Open Science Research Excellence
@article{(International Science Index):,
  title    = {Use of Fuzzy Edge Image in Block Truncation Coding for Image Compression},
  author    = {Amarunnishad T.M. and  Govindan V.K. and  Abraham T. Mathew},
  country   = {},
  abstract  = {An image compression method has been developed
using fuzzy edge image utilizing the basic Block Truncation Coding
(BTC) algorithm. The fuzzy edge image has been validated with
classical edge detectors on the basis of the results of the well-known
Canny edge detector prior to applying to the proposed method. The
bit plane generated by the conventional BTC method is replaced with
the fuzzy bit plane generated by the logical OR operation between
the fuzzy edge image and the corresponding conventional BTC bit
plane. The input image is encoded with the block mean and standard
deviation and the fuzzy bit plane. The proposed method has been
tested with test images of 8 bits/pixel and size 512×512 and found to
be superior with better Peak Signal to Noise Ratio (PSNR) when
compared to the conventional BTC, and adaptive bit plane selection
BTC (ABTC) methods. The raggedness and jagged appearance, and
the ringing artifacts at sharp edges are greatly reduced in
reconstructed images by the proposed method with the fuzzy bit
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {2},
  number    = {11},
  year      = {2008},
  pages     = {2593 - 2599},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 23, 2008},