A perceptually adaptive JPEG coder is implemented in this research. The major part of the implementation involves the design of a perceptual model that is based on the texture masking and luminance masking properties of the human visual system (HVS). The main objective is to compute a local multiplier map that can be used to scale the quantization matrix (QM) so that fewer bits are used to represent the perceptually less important areas of an image. The texture masking model is based on a proposed block classification algorithm to differentiate between the plain, edge, and texture blocks. An adaptive luminance masking scheme is also proposed which adaptively adjusts the luminance masking strategy depending on an image's mean luminance value. Experimental results show that the adaptive coder provides savings in bit-rate over baseline JPEG, with no overall loss in perceptual quality according to a subject test.
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