Spatio-Temporal Masking in Human Vision and Its Application to Image Coding.
Final technical rept.,
CALIFORNIA UNIV BERKELEY SCHOOL OF OPTOMETRY
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Before an image is stored or transmitted, we have access to the original and the distorted versions. The enhanced codec is compared to the original block by block to determine which blocks have been improved by the enhancement These blocks are then flagged for post-processing in a way that is compliant with the JPEG standard and adds nothing to the compressed images bandwidth. The end result is a compressed image that can be decompressed on any standard JPEG decompressor, but that can be enhanced by a sophisticated decompressor. For the comparison of the original and enhanced images, we have been developing a new vision model that is specifically tailored to the detection of errors that occur within or between two JPEG codec blocks. Previous filter models have been restricted from using a large number of filters due to computational constraints which we avoid by focusing the model on a tiny spatial area of 8x16 pixels. Further, features of human vision that have been included in previous models color, temporal, stereo etc. are not needed for this more focused problem. Issues that have not been completely addressed by previous models, such as masking effects, are tractable and the model is more applicable to WEG compression.