Criterios perceptuales en la compresión de imágenes

Résumé

The compression of an image is posible assuming that a portion of its information is redundant. Hence, this Ph.D. thesis proposes to exploit visual redundancy, existing in an image, reducing unperceivable frequencies for Human Visual System. First, we define an image quality assessment, which is highly correlated with the opinion of observers. The proposed metrics weights the well-known PSNR by means of a Chromatic Induction Model (CwPSNR). Second, we propose an image compression algorithm, which exploit the high correlation and self-similarity of pixels in a given area or neighborhood by means of a fractal function, called Hi-SET. Hi-SET possesses the main features that modern image compressors have, namely it is a embedded coder, which permits a progressive transmission. Also, we propose a modification to the uniform scalar quantizer, which is applied to a pixel set in a certain Wavelet sub-band. Unlike this, the proposed modification permits to perform a pixel-by-pixel forward and inverse quantization, introducing into the compression process a perceptual distortion. Finally, a coding method for Region of Interest areas is presented, pROI, which perceptually weights pixels of these areas in addition to maintain only the more important perceivable frequencies in the rest of the image. Results exposed in this thesis show that CwPSNR is the best-ranked image quality assessment, when it is compared to the most common image compression distortions such as JPEG and JPEG2000, since CwPSNR possesses the best correlation with the opinion of observers, which is based on the results of psychophysical experiments belonging to the most important image databases in this field of science such as TID2008, LIVE, CSIQ and IVC. Furthermore, Hi-SET coder obtains best results than the JPEG2000 coder and other coders that use a Hilbert Fractal for image compression. Hence, when the proposed perceptual quantization is introduced to Hi-SET coder, called PHi-SET, our compressor increments its efficiency both objective and subjective. When \pROI\ method is compared against MaxShift method of the JPEG2000 standard Part II, images coded by our method get the best results, comparing the overall image quality. Both the proposed perceptual quantization and pROI method are general algorithms that can be applied to another Wavelet based image compression algorithms such as JPEG2000, SPIHT or SPECK, for instance.