Image Restoration from Internet Transmission Corruption

In this chapter, we present a new algorithm which can remove impulse noise from corrupted images while preserving details. In Section 15.2, the algorithm is fundamentally different from the traditional methods in that it can utilize the information of not only a local window centered about the corrupted pixel but also some remote regions in the image. Experimental results indicate that our algorithm outperforms many existing techniques in Section 15.3. Its performance was analyzed in Section 15.4.

[1]  Huifang Sun,et al.  Error concealment in digital simulcast AD-HDTV decoder , 1992 .

[2]  Michael L. Lightstone,et al.  A new efficient approach for the removal of impulse noise from highly corrupted images , 1996, IEEE Trans. Image Process..

[3]  Murray H. Loew,et al.  A new approach to reduce the 'blocking effect' of transform coding [image coding] , 1993, IEEE Trans. Commun..

[4]  Kenneth E. Barner,et al.  Rank conditioned rank selection filters for signal restoration , 1994, IEEE Trans. Image Process..

[5]  Henrique S. Malvar,et al.  The LOT: transform coding without blocking effects , 1989, IEEE Trans. Acoust. Speech Signal Process..

[6]  Ming Lei Liou,et al.  Overview of the p×64 kbit/s video coding standard , 1991, CACM.

[7]  Avideh Zakhor Iterative procedures for reduction of blocking effects in transform image coding , 1992, IEEE Trans. Circuits Syst. Video Technol..

[8]  Arnaud E. Jacquin,et al.  Image coding based on a fractal theory of iterated contractive image transformations , 1992, IEEE Trans. Image Process..

[9]  Jiebo Luo,et al.  Artifact reduction in low bit rate DCT-based image compression , 1996, IEEE Trans. Image Process..

[10]  Amy R. Reibman,et al.  An error concealment algorithm for images subject to channel errors , 1995, IEEE Trans. Image Process..

[11]  Nikolas P. Galatsanos,et al.  Regularized reconstruction to reduce blocking artifacts of block discrete cosine transform compressed images , 1993, IEEE Trans. Circuits Syst. Video Technol..

[12]  Didier Le Gall,et al.  MPEG: a video compression standard for multimedia applications , 1991, CACM.

[13]  A Leon-Garcia,et al.  Information loss recovery for block-based image coding techniques-a fuzzy logic approach , 1995, IEEE Trans. Image Process..

[14]  Jae Lim,et al.  Reduction Of Blocking Effects In Image Coding , 1984 .

[15]  Yrjö Neuvo,et al.  Detail-preserving median based filters in image processing , 1994, Pattern Recognit. Lett..

[16]  Yao Wang,et al.  Signal loss recovery in DCT-based image and video codecs , 1991, Other Conferences.

[17]  Kannan Ramchandran,et al.  Nonlinear constrained least squares estimation to reduce artifacts in block transform-coded images , 1995, Proceedings., International Conference on Image Processing.

[18]  Teresa H. Y. Meng,et al.  Transform coded image reconstruction exploiting interblock correlation , 1995, IEEE Trans. Image Process..

[19]  David Zhang,et al.  Restoration of impulse noise corrupted images using long-range correlation , 1998, IEEE Signal Processing Letters.

[20]  Gregory K. Wallace,et al.  The JPEG still picture compression standard , 1991, CACM.

[21]  Huifang Sun,et al.  Concealment of damaged block transform coded images using projections onto convex sets , 1995, IEEE Trans. Image Process..

[22]  Dapeng Zhang,et al.  Impulse noise removal using polynomial approximation , 1998 .

[23]  A. Willson,et al.  Median filters with adaptive length , 1988 .

[24]  Y. Fisher Fractal image compression: theory and application , 1995 .