An Algorithm for Repairing Low-Quality Video Enhancement Techniques Based on Trained Filter

Multifarious image enhancement algorithms have been used in different applications. Still, some algorithms or modules are imperfect for practical use. When the image enhancement modules have been fixed or combined by a series of algorithms, we need to repair them as a whole part without changing the inside. This report aims to find an algorithm based on trained filters to repair low-quality image enhancement modules. A brief review on basic image enhancement techniques and pixel classification methods will be presented, and the procedure of trained filters will be described step by step. The experiments and result comparisons for this algorithm will be described in detail.

[1]  T. Berge Least squares optimization in multivariate analysis , 2005 .

[2]  G. de Haan,et al.  Simultaneous Coding Artifact Reduction and Sharpness Enhancement , 2007, 2007 Digest of Technical Papers International Conference on Consumer Electronics.

[3]  아사쿠라노부유키,et al.  Information signal processing apparatus, picture information converting apparatus, and picture displaying apparatus , 1999 .

[4]  Rafael C. González,et al.  Digital image processing, 3rd Edition , 2008 .

[5]  Isaac N. Bankman,et al.  Handbook of Medical Imaging. Processing and Analysis , 2002 .

[6]  Alan C. Bovik,et al.  Handbook of Image and Video Processing (Communications, Networking and Multimedia) , 2005 .

[7]  Mohammed Ghanbari,et al.  Scope of validity of PSNR in image/video quality assessment , 2008 .

[8]  Andrew P. Bradley,et al.  Perceptual quality metrics applied to still image compression , 1998, Signal Process..

[9]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[10]  David J. Sakrison,et al.  The effects of a visual fidelity criterion of the encoding of images , 1974, IEEE Trans. Inf. Theory.

[11]  Gerard de Haan,et al.  Coding Artifacts Robust Resolution Up-conversion , 2007, 2007 IEEE International Conference on Image Processing.

[12]  Thomas S. Huang,et al.  Image processing , 1971 .

[13]  Michael Unser,et al.  Image interpolation and resampling , 2000 .

[14]  B. Wandell,et al.  Appearance of colored patterns: pattern-color separability. , 1993, Journal of the Optical Society of America. A, Optics, image science, and vision.

[15]  Ling Shao,et al.  Content Adaptive Coding Artifact Reduction for Decompressed Video and Images , 2007, 2007 Digest of Technical Papers International Conference on Consumer Electronics.

[16]  Stefan Winkler,et al.  Issues in vision modeling for perceptual video quality assessment , 1999, Signal Process..

[17]  Himanshu Aggarwal,et al.  A Comprehensive Review of Image Enhancement Techniques , 2010, ArXiv.

[18]  Ling Shao Simultaneous coding artifact reduction and sharpness enhancement for block-based compressed images and videos , 2008, Signal Process. Image Commun..

[19]  Gerard de Haan,et al.  An Overview and Performance Evaluation of Classification-Based Least Squares Trained Filters , 2008, IEEE Transactions on Image Processing.

[20]  T.S. Perry,et al.  Consumer electronics , 1990, IEEE Spectrum.