Ingo S. Hontsch

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This paper presents a discrete cosine transform (DCT)-based locally adaptive perceptual image coder, which discriminates between image components based on their perceptual relevance for achieving increased performance in terms of quality and bit rate. The new coder uses a locally adaptive perceptual quantization scheme based on a tractable perceptual(More)
Most existing efforts in image and video compression have focused on developing methods to minimize not perceptual but rather mathematically tractable, easy to measure, distortion metrics. While nonperceptual distortion measures were found to be reasonably reliable for higher bit rates (high-quality applications), they do not correlate well with the(More)
This paper presents a perceptual-based image coder, which discriminates between image components based on their perceptual relevance for achieving increased performance in terms of quality and bit-rate. The new coder uses a locally-adaptive perceptual quantization scheme based on a tractable perceptual distortion metric. Our strategy is to exploit human(More)
This paper treats the compression of Synthetic Aperture Radar SAR imagery. SAR images are diicult to compress, relative to natural images, because SAR contains an inherent high frequency speckle. Today's state-of-the-art coders are designed to work with natural images, which h a ve a l o wer frequency content. Thus, their performance on SAR is under par. In(More)
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