Digital Cinema Watermarking State of Art and Comparison
Nowadays, the vigorous popularity of video processing techniques has resulted in an explosive growth of multimedia data illegal use. So, watermarking security has received much more attention. The purpose of this paper is to explore some watermarking techniques in order to observe their specificities and select the finest methods to apply in digital cinema domain against movie piracy by creating an invisible watermark that includes the date, time and the place where the hacking was done. We have studied three principal watermarking techniques in the frequency domain: Spread spectrum, Wavelet transform domain and finally the digital cinema watermarking transform domain. In this paper, a detailed technique is presented where embedding is performed using direct sequence spread spectrum technique in DWT transform domain. Experiment results shows that the algorithm provides high robustness and good imperceptibility.
An Analysis of Compression Methods and Implementation of Medical Images in Wireless Network
The motivation of image compression technique is to reduce the irrelevance and redundancy of the image data in order to store or pass data in an efficient way from one place to another place. There are several types of compression methods available. Without the help of compression technique, the file size is knowingly larger, usually several megabytes, but by doing the compression technique, it is possible to reduce file size up to 10% as of the original without noticeable loss in quality. Image compression can be lossless or lossy. The compression technique can be applied to images, audio, video and text data. This research work mainly concentrates on methods of encoding, DCT, compression methods, security, etc. Different methodologies and network simulations have been analyzed here. Various methods of compression methodologies and its performance metrics has been investigated and presented in a table manner.
A Way of Converting Color Images to Gray Scale Ones for the Color-Blind -Applying to the Part of the Tokyo Subway Map-
This paper proposes a way of removing noises and reducing the number of colors contained in a JPEG image. Main purpose of this project is to convert color images to monochrome images for the color-blind. We treat the crispy color images like the Tokyo subway map. Each color in the image has an important information. But for the color blinds, similar colors cannot be distinguished. If we can convert those colors to different gray values, they can distinguish them. Therefore we try to convert color images to monochrome images.
Perceptual JPEG Compliant Coding by Using DCT-Based Visibility Thresholds of Color Images
Effective estimation of just noticeable distortion (JND) for images is helpful to increase the efficiency of a compression algorithm in which both the statistical redundancy and the perceptual redundancy should be accurately removed. In this paper, we design a DCT-based model for estimating JND profiles of color images. Based on a mathematical model of measuring the base detection threshold for each DCT coefficient in the color component of color images, the luminance masking adjustment, the contrast masking adjustment, and the cross masking adjustment are utilized for luminance component, and the variance-based masking adjustment based on the coefficient variation in the block is proposed for chrominance components. In order to verify the proposed model, the JND estimator is incorporated into the conventional JPEG coder to improve the compression performance. A subjective and fair viewing test is designed to evaluate the visual quality of the coding image under the specified viewing condition. The simulation results show that the JPEG coder integrated with the proposed DCT-based JND model gives better coding bit rates at visually lossless quality for a variety of color images.
FPGA Hardware Implementation and Evaluation of a Micro-Network Architecture for Multi-Core Systems
This paper presents the design, implementation and evaluation of a micro-network, or Network-on-Chip (NoC), based on a generic pipeline router architecture. The router is designed to efficiently support traffic generated by multimedia applications on embedded multi-core systems. It employs a simplest routing mechanism and implements the round-robin scheduling strategy to resolve output port contentions and minimize latency. A virtual channel flow control is applied to avoid the head-of-line blocking problem and enhance performance in the NoC. The hardware design of the router architecture has been implemented at the register transfer level; its functionality is evaluated in the case of the two dimensional Mesh/Torus topology, and performance results are derived from ModelSim simulator and Xilinx ISE 9.2i synthesis tool. An example of a multi-core image processing system utilizing the NoC structure has been implemented and validated to demonstrate the capability of the proposed micro-network architecture. To reduce complexity of the image compression and decompression architecture, the system use image processing algorithm based on classical discrete cosine transform with an efficient zonal processing approach. The experimental results have confirmed that both the proposed image compression scheme and NoC architecture can achieve a reasonable image quality with lower processing time.
A Way of Converting Color Images to Gray Scale Ones for the Color Blinds -Reducing the Colors for Tokyo Subway Map-
We proposes a way of removing noises and reducing the number of colors contained in a JPEG image. Main purpose of this project is to convert color images to monochrome images for the color blinds. We treat the crispy color images like the Tokyo subway map. Each color in the image has an important information. But for the color blinds, similar colors cannot be distinguished. If we can convert those colors to different gray values, they can distinguish them.
Maximizer of the Posterior Marginal Estimate for Noise Reduction of JPEG-compressed Image
We constructed a method of noise reduction for
JPEG-compressed image based on Bayesian inference using the
maximizer of the posterior marginal (MPM) estimate. In this method,
we tried the MPM estimate using two kinds of likelihood, both of
which enhance grayscale images converted into the JPEG-compressed
image through the lossy JPEG image compression. One is the
deterministic model of the likelihood and the other is the probabilistic
one expressed by the Gaussian distribution. Then, using the Monte
Carlo simulation for grayscale images, such as the 256-grayscale
standard image “Lena" with 256 × 256 pixels, we examined the
performance of the MPM estimate based on the performance measure
using the mean square error. We clarified that the MPM estimate via
the Gaussian probabilistic model of the likelihood is effective for
reducing noises, such as the blocking artifacts and the mosquito noise,
if we set parameters appropriately. On the other hand, we found that
the MPM estimate via the deterministic model of the likelihood is not
effective for noise reduction due to the low acceptance ratio of the
Coding of DWT Coefficients using Run-length Coding and Huffman Coding for the Purpose of Color Image Compression
In present paper we proposed a simple and effective method to compress an image. Here we found success in size reduction of an image without much compromising with it-s quality. Here we used Haar Wavelet Transform to transform our original image and after quantization and thresholding of DWT coefficients Run length coding and Huffman coding schemes have been used to encode the image. DWT is base for quite populate JPEG 2000 technique.
Design of a DCT-based Image Compression with Efficient Enhancement Filter
The algorithm represents the DCT coefficients to concentrate signal energy and proposes combination and dictator to eliminate the correlation in the same level subband for encoding the DCT-based images. This work adopts DCT and modifies the SPIHT algorithm to encode DCT coefficients. The proposed algorithm also provides the enhancement function in low bit rate in order to improve the perceptual quality. Experimental results indicate that the proposed technique improves the quality of the reconstructed image in terms of both PSNR and the perceptual results close to JPEG2000 at the same bit rate.
A Novel VLSI Architecture for Image Compression Model Using Low power Discrete Cosine Transform
In Image processing the Image compression can improve
the performance of the digital systems by reducing the cost and
time in image storage and transmission without significant reduction
of the Image quality. This paper describes hardware architecture of
low complexity Discrete Cosine Transform (DCT) architecture for
image compression. In this DCT architecture, common computations
are identified and shared to remove redundant computations
in DCT matrix operation. Vector processing is a method used for
implementation of DCT. This reduction in computational complexity
of 2D DCT reduces power consumption. The 2D DCT is performed
on 8x8 matrix using two 1-Dimensional Discrete cosine transform
blocks and a transposition memory . Inverse discrete cosine
transform (IDCT) is performed to obtain the image matrix and
reconstruct the original image. The proposed image compression
algorithm is comprehended using MATLAB code. The VLSI design
of the architecture is implemented Using Verilog HDL. The proposed
hardware architecture for image compression employing DCT was
synthesized using RTL complier and it was mapped using 180nm
standard cells. . The Simulation is done using Modelsim. The
simulation results from MATLAB and Verilog HDL are compared.
Detailed analysis for power and area was done using RTL compiler
from CADENCE. Power consumption of DCT core is reduced to
1.027mW with minimum area.
RADAR Imaging to Develop an Enhanced Fog Vision System for Collision Avoidance
The scattering effect of light in fog improves the
difficulty in visibility thus introducing disturbances in transport
facilities in urban or industrial areas causing fatal accidents or public
harassments, therefore, developing an enhanced fog vision system
with radio wave to improvise the way outs of these severe problems
is really a big challenge for researchers. Series of experimental
studies already been done and more are in progress to know the
weather effect on radio frequencies for different ranges. According to
Rayleigh scattering Law, the propagating wavelength should be
greater than the diameter of the particle present in the penetrating
medium. Direct wave RF signal thus have high chance of failure to
work in such weather for detection of any object. Therefore an
extensive study was required to find suitable region in the RF band
that can help us in detecting objects with proper shape. This paper
produces some results on object detection using 912 MHz band with
successful detection of the persistence of any object coming under the
trajectory of a vehicle navigating in indoor and outdoor environment.
The developed images are finally transformed to video signal to
enable continuous monitoring.
An Algorithm for Secure Visible Logo Embedding and Removing in Compression Domain
Digital watermarking is the process of embedding
information into a digital signal which can be used in DRM (digital
rights managements) system. The visible watermark (often called logo)
can indicate the owner of the copyright which can often be seen in the
TV program and protects the copyright in an active way. However,
most of the schemes do not consider the visible watermark removing
process. To solve this problem, a visible watermarking scheme with
embedding and removing process is proposed under the control of a
secure template. The template generates different version of
watermarks which can be seen visually the same for different users.
Users with the right key can completely remove the watermark and
recover the original image while the unauthorized user is prevented to
remove the watermark. Experiment results show that our
watermarking algorithm obtains a good visual quality and is hard to be
removed by the illegally users. Additionally, the authorized users can
completely remove the visible watermark and recover the original
image with a good quality.
EZW Coding System with Artificial Neural Networks
Image compression plays a vital role in today-s
communication. The limitation in allocated bandwidth leads to
slower communication. To exchange the rate of transmission in the
limited bandwidth the Image data must be compressed before
transmission. Basically there are two types of compressions, 1)
LOSSY compression and 2) LOSSLESS compression. Lossy
compression though gives more compression compared to lossless
compression; the accuracy in retrievation is less in case of lossy
compression as compared to lossless compression. JPEG, JPEG2000
image compression system follows huffman coding for image
compression. JPEG 2000 coding system use wavelet transform,
which decompose the image into different levels, where the
coefficient in each sub band are uncorrelated from coefficient of
other sub bands. Embedded Zero tree wavelet (EZW) coding exploits
the multi-resolution properties of the wavelet transform to give a
computationally simple algorithm with better performance compared
to existing wavelet transforms. For further improvement of
compression applications other coding methods were recently been
suggested. An ANN base approach is one such method. Artificial
Neural Network has been applied to many problems in image
processing and has demonstrated their superiority over classical
methods when dealing with noisy or incomplete data for image
compression applications. The performance analysis of different
images is proposed with an analysis of EZW coding system with
Error Backpropagation algorithm. The implementation and analysis
shows approximately 30% more accuracy in retrieved image
compare to the existing EZW coding system.
Fast Cosine Transform to Increase Speed-up and Efficiency of Karhunen-Loève Transform for Lossy Image Compression
In this work, we present a comparison between two
techniques of image compression. In the first case, the image is
divided in blocks which are collected according to zig-zag scan. In
the second one, we apply the Fast Cosine Transform to the image,
and then the transformed image is divided in blocks which are
collected according to zig-zag scan too. Later, in both cases, the
Karhunen-Loève transform is applied to mentioned blocks. On the
other hand, we present three new metrics based on eigenvalues for a
better comparative evaluation of the techniques. Simulations show
that the combined version is the best, with minor Mean Absolute
Error (MAE) and Mean Squared Error (MSE), higher Peak Signal to
Noise Ratio (PSNR) and better image quality. Finally, new technique
was far superior to JPEG and JPEG2000.
A Complexity-Based Approach in Image Compression using Neural Networks
In this paper we present an adaptive method for image
compression that is based on complexity level of the image. The
basic compressor/de-compressor structure of this method is a multilayer
perceptron artificial neural network. In adaptive approach
different Back-Propagation artificial neural networks are used as
compressor and de-compressor and this is done by dividing the
image into blocks, computing the complexity of each block and then
selecting one network for each block according to its complexity
value. Three complexity measure methods, called Entropy, Activity
and Pattern-based are used to determine the level of complexity in
image blocks and their ability in complexity estimation are evaluated
and compared. In training and evaluation, each image block is
assigned to a network based on its complexity value. Best-SNR is
another alternative in selecting compressor network for image blocks
in evolution phase which chooses one of the trained networks such
that results best SNR in compressing the input image block. In our
evaluations, best results are obtained when overlapping the blocks is
allowed and choosing the networks in compressor is based on the
Best-SNR. In this case, the results demonstrate superiority of this
method comparing with previous similar works and JPEG standard
A DCT-Based Secure JPEG Image Authentication Scheme
The challenge in the case of image authentication is that in many cases images need to be subjected to non malicious operations like compression, so the authentication techniques need to be compression tolerant. In this paper we propose an image authentication system that is tolerant to JPEG lossy compression operations. A scheme for JPEG grey scale images is proposed based on a data embedding method that is based on a secret key and a secret mapping vector in the frequency domain. An encrypted feature vector extracted from the image DCT coefficients, is embedded redundantly, and invisibly in the marked image. On the receiver side, the feature vector from the received image is derived again and compared against the extracted watermark to verify the image authenticity. The proposed scheme is robust against JPEG compression up to a maximum compression of approximately 80%,, but sensitive to malicious attacks such as cutting and pasting.
A Novel VLSI Architecture of Hybrid Image Compression Model based on Reversible Blockade Transform
Image compression can improve the performance of
the digital systems by reducing time and cost in image storage
and transmission without significant reduction of the image quality.
Furthermore, the discrete cosine transform has emerged as the new
state-of-the art standard for image compression. In this paper, a
hybrid image compression technique based on reversible blockade
transform coding is proposed. The technique, implemented over
regions of interest (ROIs), is based on selection of the coefficients
that belong to different transforms, depending on the coefficients is
proposed. This method allows: (1) codification of multiple kernals
at various degrees of interest, (2) arbitrary shaped spectrum,and (3)
flexible adjustment of the compression quality of the image and the
background. No standard modification for JPEG2000 decoder was
required. The method was applied over different types of images.
Results show a better performance for the selected regions, when
image coding methods were employed for the whole set of images.
We believe that this method is an excellent tool for future image
compression research, mainly on images where image coding can
be of interest, such as the medical imaging modalities and several
multimedia applications. Finally VLSI implementation of proposed
method is shown. It is also shown that the kernal of Hartley and
Cosine transform gives the better performance than any other model.
Low-MAC FEC Controller for JPEG2000 Image Transmission Over IEEE 802.15.4
In this paper, we propose the low-MAC FEC controller for practical implementation of JPEG2000 image transmission using IEEE 802.15.4. The proposed low-MAC FEC controller has very small HW size and spends little computation to estimate channel state. Because of this advantage, it is acceptable to apply IEEE 802.15.4 which has to operate more than 1 year with battery. For the image transmission, we integrate the low-MAC FEC controller and RCPC coder in sensor node of LR-WPAN. The modified sensor node has increase of 3% hardware size than conventional zigbee sensor node.
A Secure Semi-Fragile Watermarking Scheme for Authentication and Recovery of Images Based On Wavelet Transform
Authentication of multimedia contents has gained much attention in recent times. In this paper, we propose a secure semi-fragile watermarking, with a choice of two watermarks to be embedded. This technique operates in integer wavelet domain and makes use of semi fragile watermarks for achieving better robustness. A self-recovering algorithm is employed, that hides the image digest into some Wavelet subbands to detect possible malevolent object manipulation undergone by the image (object replacing and/or deletion). The Semi-fragility makes the scheme tolerant for JPEG lossy compression as low as quality of 70%, and locate the tempered area accurately. In addition, the system ensures more security because the embedded watermarks are protected with private keys. The computational complexity is reduced using parameterized integer wavelet transform. Experimental results show that the proposed scheme guarantees the safety of watermark, image recovery and location of the tempered area accurately.
Robust Digital Cinema Watermarking
With the advent of digital cinema and digital
broadcasting, copyright protection of video data has been one of the
most important issues.
We present a novel method of watermarking for video image data
based on the hardware and digital wavelet transform techniques and
name it as “traceable watermarking" because the watermarked data is
constructed before the transmission process and traced after it has been
received by an authorized user.
In our method, we embed the watermark to the lowest part of each
image frame in decoded video by using a hardware LSI.
Digital Cinema is an important application for traceable
watermarking since digital cinema system makes use of watermarking
technology during content encoding, encryption, transmission,
decoding and all the intermediate process to be done in digital cinema
systems. The watermark is embedded into the randomly selected
movie frames using hash functions.
Embedded watermark information can be extracted from the
decoded video data. For that, there is no need to access original movie
data. Our experimental results show that proposed traceable
watermarking method for digital cinema system is much better than the
convenient watermarking techniques in terms of robustness, image
quality, speed, simplicity and robust structure.
Performance Analysis of Chrominance Red and Chrominance Blue in JPEG
While compressing text files is useful, compressing
still image files is almost a necessity. A typical image takes up much
more storage than a typical text message and without compression
images would be extremely clumsy to store and distribute. The
amount of information required to store pictures on modern
computers is quite large in relation to the amount of bandwidth
commonly available to transmit them over the Internet and
applications. Image compression addresses the problem of reducing
the amount of data required to represent a digital image. Performance
of any image compression method can be evaluated by measuring the
root-mean-square-error & peak signal to noise ratio. The method of
image compression that will be analyzed in this paper is based on the
lossy JPEG image compression technique, the most popular
compression technique for color images. JPEG compression is able to
greatly reduce file size with minimal image degradation by throwing
away the least “important" information. In JPEG, both color
components are downsampled simultaneously, but in this paper we
will compare the results when the compression is done by
downsampling the single chroma part. In this paper we will
demonstrate more compression ratio is achieved when the
chrominance blue is downsampled as compared to downsampling the
chrominance red in JPEG compression. But the peak signal to noise
ratio is more when the chrominance red is downsampled as compared
to downsampling the chrominance blue in JPEG compression. In
particular we will use the hats.jpg as a demonstration of JPEG
compression using low pass filter and demonstrate that the image is
compressed with barely any visual differences with both methods.
New Features for Specific JPEG Steganalysis
We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also control the alteration of the compressed data. We have noticed a deviation of the entropy of the compressed data after a first embedding. This deviation is greater when the image is a cover medium than when the image is a stego image. To observe this deviation, we pointed out new statistic features and combined them with the Multiple Embedding Method. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. Finally, we designed a Fisher discriminant based classifier for well known steganographic algorithms, Outguess, F5 and Hide and Seek. The experiemental results we obtained show the efficiency of our classifier for these algorithms. Moreover, it is also designed to work with low embedding rates (< 10-5) and according to the avalanche criterion of RLE and Huffman compression step, its efficiency is independent of the quantity of hidden information.
Design Techniques and Implementation of Low Power High-Throughput Discrete Wavelet Transform Tilters for JPEG 2000 Standard
In this paper, the implementation of low power,
high throughput convolutional filters for the one dimensional
Discrete Wavelet Transform and its inverse are presented. The
analysis filters have already been used for the implementation of a
high performance DWT encoder  with minimum memory
requirements for the JPEG 2000 standard. This paper presents the
design techniques and the implementation of the convolutional filters
included in the JPEG2000 standard for the forward and inverse DWT
for achieving low-power operation, high performance and reduced
memory accesses. Moreover, they have the ability of performing
progressive computations so as to minimize the buffering between
the decomposition and reconstruction phases. The experimental
results illustrate the filters- low power high throughput characteristics
as well as their memory efficient operation.
Traceable Watermarking System using SoC for Digital Cinema Delivery
As the development of digital technology is increasing,
Digital cinema is getting more spread.
However, content copy and attack against the digital cinema becomes
a serious problem. To solve the above security problem, we propose
“Additional Watermarking" for digital cinema delivery system. With
this proposed “Additional watermarking" method, we protect content
copyrights at encoder and user side information at decoder. It realizes
the traceability of the watermark embedded at encoder.
The watermark is embedded into the random-selected frames using
Hash function. Using it, the embedding position is distributed by Hash
Function so that third parties do not break off the watermarking
Finally, our experimental results show that proposed method is much
better than the convenient watermarking techniques in terms of
robustness, image quality and its simple but unbreakable algorithm.
Objective Performance of Compressed Image Quality Assessments
Measurement of the quality of image compression is important for image processing application. In this paper, we propose an objective image quality assessment to measure the quality of gray scale compressed image, which is correlation well with subjective quality measurement (MOS) and least time taken. The new objective image quality measurement is developed from a few fundamental of objective measurements to evaluate the compressed image quality based on JPEG and JPEG2000. The reliability between each fundamental objective measurement and subjective measurement (MOS) is found. From the experimental results, we found that the Maximum Difference measurement (MD) and a new proposed measurement, Structural Content Laplacian Mean Square Error (SCLMSE), are the suitable measurements that can be used to evaluate the quality of JPEG200 and JPEG compressed image, respectively. In addition, MD and SCLMSE measurements are scaled to make them equivalent to MOS, given the rate of compressed image quality from 1 to 5 (unacceptable to excellent quality).
Detection of Breast Cancer in the JPEG2000 Domain
Breast cancer detection techniques have been reported
to aid radiologists in analyzing mammograms. We note that most
techniques are performed on uncompressed digital mammograms.
Mammogram images are huge in size necessitating the use of
compression to reduce storage/transmission requirements. In this
paper, we present an algorithm for the detection of
microcalcifications in the JPEG2000 domain. The algorithm is based
on the statistical properties of the wavelet transform that the
JPEG2000 coder employs. Simulation results were carried out at
different compression ratios. The sensitivity of this algorithm ranges
from 92% with a false positive rate of 4.7 down to 66% with a false
positive rate of 2.1 using lossless compression and lossy compression
at a compression ratio of 100:1, respectively.
DWT Based Robust Watermarking Embed Using CRC-32 Techniques
As far as the latest technological improvements are concerned, digital systems more become popular than the past. Despite this growing demand to the digital systems, content copy and attack against the digital cinema contents becomes a serious problem. To solve the above security problem, we propose “traceable watermarking using Hash functions for digital cinema system. Digital Cinema is a great application for traceable watermarking since it uses watermarking technology during content play as well as content transmission. The watermark is embedded into the randomly selected movie frames using CRC-32 techniques. CRC-32 is a Hash function. Using it, the embedding position is distributed by Hash Function so that any party cannot break off the watermarking or will not be able to change. Finally, our experimental results show that proposed DWT watermarking method using CRC-32 is much better than the convenient watermarking techniques in terms of robustness, image quality and its simple but unbreakable algorithm.
Parallel Image Compression and Analysis with Wavelets
This paper presents image compression with wavelet based method. The wavelet transformation divides image to low- and high pass filtered parts. The traditional JPEG compression technique requires lower computation power with feasible losses, when only compression is needed. However, there is obvious need for wavelet based methods in certain circumstances. The methods are intended to the applications in which the image analyzing is done parallel with compression. Furthermore, high frequency bands can be used to detect changes or edges. Wavelets enable hierarchical analysis for low pass filtered sub-images. The first analysis can be done for a small image, and only if any interesting is found, the whole image is processed or reconstructed.