A smoothness constraint set based on local statistics of BDCT coefficients for image postprocessing

  • Authors:

  • Xiangchao Gan;Alan Wee-Chung Liew;Hong Yan

  • Affiliations:

  • Department of Computer Engineering and Information Technology, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China;Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China;Department of Computer Engineering and Information Technology, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China and School of Electrical and Information Engineering, Uni ...

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2005

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Abstract

In blocking artifacts reduction based on the projection onto convex sets (POCS) technique, good constraint sets are very important. Until recently, smoothness constraint sets (SCS) are often formulated in the image domain, whereas quantization constraint set is defined in the block-based discrete cosine transform (BDCT) domain. Thus, frequent BDCT transform is inevitable in alternative projections. In this paper, based on signal and quantization noise statistics, we proposed a novel smoothness constraint set in the BDCT transform domain via the Wiener filtering concept. Experiments show that POCS using this smoothness constraint set not only has good convergence but also has better objective and subjective performance. Moreover, this set can be used as extra constraint set to improve most existing POCS-based image postprocessing methods.