Block-based histogram packing of color-quantized images
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
A new steganographic method for color and grayscale image hiding
Computer Vision and Image Understanding
Semantic quantization of 3D human motion capture data through spatial-temporal feature extraction
MMM'08 Proceedings of the 14th international conference on Advances in multimedia modeling
Knowledge discovery from 3D human motion streams through semantic dimensional reduction
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
An improved spectral clustering algorithm based on random walk
Frontiers of Computer Science in China
Color quantization of digital images
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part II
NPAR '12 Proceedings of the Symposium on Non-Photorealistic Animation and Rendering
An efficient color quantization based on generic roughness measure
Pattern Recognition
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Image quantization and digital halftoning, two fundamental image processing problems, are generally performed sequentially and, in most cases, independent of each other. Color reduction with a pixel-wise defined distortion measure and the halftoning process with its local averaging neighborhood typically optimize different quality criteria or, frequently, follow a heuristic approach without reference to any quantitative quality measure. In this paper, we propose a new model to simultaneously quantize and halftone color images. The method is based on a rigorous cost-function approach which optimizes a quality criterion derived from a simplified model of human perception. It incorporates spatial and contextual information into the quantization and thus overcomes the artificial separation of quantization and halftoning. Optimization is performed by an efficient multiscale procedure which substantially alleviates the computational burden. The quality criterion and the optimization algorithms are evaluated on a representative set of artificial and real-world images showing a significant image quality improvement compared to standard color reduction approaches. Applying the developed cost function, we also suggest a new distortion measure for evaluating the overall quality of color reduction schemes