Paper
5 November 2020 Image denoising via adaptive dictionary learning based on single-pixel imaging
Ziran Wei, Jianlin Zhang, Zhiyong Xu, Yong Liu
Author Affiliations +
Proceedings Volume 11567, AOPC 2020: Optical Sensing and Imaging Technology; 1156711 (2020) https://doi.org/10.1117/12.2576356
Event: Applied Optics and Photonics China (AOPC 2020), 2020, Beijing, China
Abstract
Based on the principle of compressed sensing, a single-pixel imaging system (single-pixel camera) was built in our laboratory, and our single-pixel camera can successfully acquire the picture of imaging scene of a distant building. However, the process of single-pixel imaging is easily disturbed by noise. In order to reduce the interference of noise in the imaging results as much as possible, we apply the method of adaptive dictionary learning to denoise the reconstructed image in our single-pixel camera. The block-coordinate decent idea and K-SVD algorithm are used to complete the dictionary learning by training on the noisy reconstructed image in the method of block-by-block scanning, which doesn’t require the extra corpus of image patches, so the method of dictionary learning is self-adaptive to the imaging picture that need to be denoised. The overcomplete DWT (discrete wavelet transform) dictionary is applied as the known initial dictionary that will be trained in the adaptive dictionary learning. The effectiveness of the adaptive dictionary learning has been demonstrated by the simulation experiment and the practical imaging experiment, the method of adaptive dictionary learning based on the initialization of overcomplete DWT dictionary effectively reduces the imaging noise and improves the image reconstruction accuracy and imaging quality.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ziran Wei, Jianlin Zhang, Zhiyong Xu, and Yong Liu "Image denoising via adaptive dictionary learning based on single-pixel imaging", Proc. SPIE 11567, AOPC 2020: Optical Sensing and Imaging Technology, 1156711 (5 November 2020); https://doi.org/10.1117/12.2576356
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KEYWORDS
Cameras

Reconstruction algorithms

Discrete wavelet transforms

Image restoration

Compressed sensing

Denoising

Image quality

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