Optimization of JPEG color image coding using a human visual system model

We introduce a new model that can be used in the perceptual optimization of standard color image coding algorithms (JPEG/MPEG). The human visual system model is based on a set of oriented filters and incorporates background luminance dependencies, luminance and chrominance frequency sensitivities, and luminance and chrominance masking effects. The main problem in using oriented filter-based models for the optimization of coding algorithms is the difference between the orientation of the filters in the model domain and the DCT block transform in decoding domain. We propose a general method to combine these domains by calculating a local sensitivity for each DCT (color) block. This leads to a perceptual weighting factor for each DCT coefficient in each block. We show how these weighting factors allow us to use advanced techniques for optimal bit allocation in JPEG (e.g. custom quantization matrix design and adaptive thresholding). With the model we propose it is possible to calculate a perceptually weighted mean squared error (WMSE) directly in the DCT color domain, although the model itself is based on a directional frequency band decomposition.