A Review on GCD Updates Detectablity, and Optimized Methods for Foveated Image & Video Coding

This paper reviews a Perceptually Optimized Foveation based Embedded ZeroTree Image Coder (POEFIC) that introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement. The study also, provides a new objective quality metric based on a Psychovisual model that incorporates the properties of the HVS, plays an important role in this POEFIC quality evaluation. The perceptual weights for all wavelet subbands are computed based on 1) foveation masking to remove or diminish significant high frequencies from peripheral regions 2) luminance and Contrast masking, 3) the contrast sensitivity function CSF to attain the perceptual decomposition weighting. On the other hand, image and video coding is an optimization problem. A successful image and video coding algorithm conveys a good tradeoff between visual quality and other coding performance measures, such as robustness, complexity, compression, scalability, and security. This review pursues two recent styles in image and video coding research. One is to integrate human visual system (HVS) models to progress the current stateof-the-art of image and video coding algorithms by better utilizing the properties of the projected receiver. The other is to design rate scalable image and video codecs, which allow the extraction of coded visual information at continuously altering bit rates from a single compressed bitstream. Prior to aforesaid studies, this paper reviews the work has been done to answer the question “how late can you update gazecontingent multiresolutional displays without detection?”.