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We study different quantization schemes for the Compressed Histogram of Gradients (CHoG) image feature descriptor. We propose a scheme for compressing distributions called Type Coding, which offers lower complexity and higher compression efficiency compared to tree-based quantization schemes proposed in prior work. We construct optimal Entropy Constrained Vector Quantization (ECVQ) code-books and...
Local features are widely used for content-based image retrieval and object recognition. We present an efficient method for encoding digital images suitable for local feature extraction. First, we find the patches in the image corresponding to the detected features. Then, we extract these patches at their characteristic scale and orientation and encode them for efficient transmission. A Discrete Cosine...
Wyner-Ziv coding of multiview images avoids communications between source cameras. To achieve good compression performance, the decoder must relate the source and side information images. Since correlation between the two images is exploited at the bit level, it is desirable to map small Euclidean distances between coefficients into small Hamming distances between bitwise codewords. This important...
Wyner-Ziv coding of multiview images is an attractive solution because it avoids communications between individual cameras. To achieve good rate-distortion performance, the Wyner-Ziv decoder must reliably estimate the disparities between the multiview images. For the scenario where two reference images exist at the decoder, we propose a codec that effectively performs unsupervised learning of the...
Distributed coding of correlated grayscale stereo images is effectively addressed by a recently proposed codec that learns block-wise disparity at the decoder. Based on the Slepian-Wolf theorem, one image can be transmitted at a rate approaching the conditional entropy if the other image is referenced as side information at the decoder. This paper improves the methods in the decoder design by refining...
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