Abstract

In this paper, a novel geometric transform, called the valley transform (VT), is proposed for robust compression of noisy images. The VT employs a nonlinear transform to convert random signals into regular ones. The proposed VT is able to change random pixels to regular one. For testing the compression performance, the VT is combined with the SPHIT method. The VT yields slightly better performance than the conventional image codecs such as JBIG, HD-photo and H.264 intra method in the lower bit-plane image compression.

Keywords:
Lossless compression Lossy compression Artificial intelligence Computer science Transform coding Data compression Image compression Compression (physics) Computer vision Pixel Codec Texture compression Algorithm Image (mathematics) Image processing Discrete cosine transform Telecommunications Materials science

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Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Digital Filter Design and Implementation
Physical Sciences →  Computer Science →  Signal Processing

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