An efficient psychovisual threshold technique in image compression

Nowadays, psychovisual model plays a critical role in an image compression system. The psychovisual threshold gives visual tolerance to the human visual system by reducing the amount of frequency image signals. The sensitivity of the human eye can be fully explored and exploited in the qualitative experiment by describing what has been seen or by image quality judgment. However, the result of the psychovisual threshold through qualitative experiment depends on the test condition of the human visual systems and through repetitive viewing sessions. In a modern image compression, there is a need to provide some flexibility to obtain quality levels of the image output based on user preferences. The concept of psychovisual threshold is designed to determine quality levels of the image output. The psychovisual threshold represents an optimal amount of frequency image signals in image compression. This research proposes the psychovisual threshold through a quantitative experiment that can automatically predict an optimal balance between image quality and compression rate in image compression. The contribution of its frequency image signals to the image reconstruction will be the primitive of psychovisual threshold in image compression. It is very challenging to develop a psychovisual threshold from the contribution of the frequency image signals for each frequency order. In this research, the psychovisual threshold prescribes the quantization values and bit allocation for image compression. The psychovisual threshold is the basic primitive prior to generating quantization tables in image compression. The psychovisual threshold allows a developer to design adaptively customized quantization values according to his or her target image quality. The psychovisual threshold is also elementary and primitive for generating a set of bit allocation for frequency image signals. A set of bit allocation based on psychovisual threshold assigns the amount of bits for frequency image signals. A set of bit allocation refers to the psychovisual threshold instead of the quantization process in image compression. This research investigates the basic understanding of the psychovisual threshold in image compression. The experimental results provide significant improvement in the image compression. The psychovisual threshold which is presented as quantization tables, customized quantization tables and as a set of bit allocation gives a significant improvement on both of the quality of the image reconstruction and the average bit length of Huffman code. This research shows that psychovisual threshold is practically the best measure for optimal frequency image signals on image compression

Psychovisual Threshold On Large Tchebichef Moment For Image Compression

JPEG standard transforms an 8×8 image pixel into a requency domain. The discontinuities of the intensity image between adjacent image blocks cause the visual artifacts due to inter-block correlations in image reconstruction. The blocking artifacts appear by the pixel intensity value discontinuities which occur along block boundaries. This research proposes the psychovisual threshold on large Tchebichef moment to minimize the blocking artifacts. The psychovisual threshold is practically the best measure for the optimal amount of frequency image signals in the image coding. The psychovisual threshold is a basic element prior to generating quantization tables in image compression. The psychovisual threshold on the large Tchebichef moments has given significant improvements in the quality of image output. The experimental results show that the smooth psychovisual threshold on the large discrete Tchebichef moment produces high quality image output and largely free of any visual artifacts

A Psychovisual Threshold For Generating Quantization Process In Tchebichef Moment Image Compression

A human visual system can hardly respond to small differences in image signals. A full colour image carries a certain amount of perceptual redundancy for the human eyes. The sensitivity human eye of the color image can be measured by a psychovisual threshold. The sensitivity of the human eye is useful for perceptual visual image in image compression. The quantization tables are obtained to determine psychovisual threshold that can be perceived visually significant by the human eye. This paper introduces the concept of psychovisual threshold into Tchebichef moment image compression. This paper will investigate the contribution of each moment coefficient to the image reconstruction. The error threshold from the contribution of its moments in image reconstruction will be the primitive of psychovisual threshold to an image. This paper presents a new technique to generate quantization table for an optimal TMT image compression based on psychovisual error threshold. The experimental results show that these new finer quantization tables provide a statistically better image quality output at lower average bit length of Huffman's code than previously proposed TMT quantization