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- W1967993666 abstract "Local features are widely used for content-based image retrieval and object recognition. Most feature descriptors are calculated from the gradients of a canonical patch around repeatable keypoints in the image. In this paper, we propose a technique for designing quantization matrices that reduce the mean squared error distortion of the gradient derived from DCT-encoded canonical patches. Experimental results demonstrate that our proposed patch encoder greatly outperforms a JPEG encoder at the same encoding complexity. Moreover, our quantization matrices achieve lower gradient distortion and larger number of feature matches at the same bit-rate." @default.
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- W1967993666 date "2012-09-01" @default.
- W1967993666 modified "2023-09-26" @default.
- W1967993666 title "Gradient preserving quantization" @default.
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- W1967993666 doi "https://doi.org/10.1109/icip.2012.6467407" @default.
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