Lossless Image Compression Based on Contextual Adaptation of Predictor Blends (CROSBI ID 642261)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa
Podaci o odgovornosti
Knezović, Josip ; Žagar, Martin ; Kovač, Mario
engleski
Lossless Image Compression Based on Contextual Adaptation of Predictor Blends
Lossless compression of visual data is required in applications such as medical imaging, image archival, remote and satellite imaging etc. We present a new adaptive predictive image coding method based on the blending of multiple static predictors on a dynamically classified causal context of neighboring pixels. The idea of predictor blends is further expanded through the determination of blending context that changes its shape on a pixel--by--pixel basis using simple classification technique, thus allowing the modeling more complex image structures such as nontrivially oriented edges, the periodicity and coarseness of textures. Typical natural images are characterized as being composed of image regions with different local properties. The predictor estimates those properties around the currently unknown pixel and adjusts itself so that the presence of detected properties affect the way the final prediction is made. Predictive part is followed by a heuristic contextual model and statistical encoder.
lossless image compression; image coding; predictive coding; predictor blends; statistical coding
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Podaci o prilogu
11-11.
2012.
objavljeno
Podaci o matičnoj publikaciji
First Croatian Computer Vision Workshop 2012. Abstract Book
Zagreb: Center of Excellence for Computer Vision, University of Zagreb
Podaci o skupu
First Croatian Computer Vision Workshop
predavanje
20.09.2012-21.09.2012
Zagreb, Hrvatska