Blind image quality evaluation of gradient oriented compressed coded aperture imaging

Yuantian Lei; Tinghua Zhang; Chunyang Li; Houpeng Sun

doi:10.1117/12.2606503

29 December 2021 Blind image quality evaluation of gradient oriented compressed coded aperture imaging

Yuantian Lei, Tinghua Zhang, Chunyang Li, Houpeng Sun

Proceedings Volume 12065, AOPC 2021: Optical Sensing and Imaging Technology; 1206540 (2021) https://doi.org/10.1117/12.2606503
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

Compressed sensing theory is a new sampling theory, which provides a method to recover the original signal from a small number of samples. For sparse signal and compressible signal, compressed sensing theory compresses the signal while sampling. It combines the sampling process and compression process. It breaks through the traditional Nyquist sampling law and saves a lot of storage, transmission, computing and other resources. This theory not only reduces the cost of storage and transmission of digital image and video acquisition, but also provides a new opportunity for the follow-up research of image processing and recognition, and promotes the combination of theory and engineering application. It includes three parts: sparse representation of target, design of measurement matrix and reconstruction of target. Reconstruction algorithm is a key step in the process of compression imaging, which determines the accuracy and speed of image reconstruction to a certain extent, so it is very important to select the appropriate image quality evaluation index. The image quality evaluation of existing reconstruction algorithms mainly focuses on peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The advantages of these two algorithms lie in simple algorithm, fast inspection speed, which are suitable for evaluating the advantages and disadvantages of algorithms, but the disadvantage is that they can only be evaluated on the basis of known original images. In the actual imaging process of compressed sensing, it is impossible to obtain the original image, so we need to use an image quality evaluation method which is not based on the original image.

Citation Download Citation

Yuantian Lei, Tinghua Zhang, Chunyang Li, and Houpeng Sun "Blind image quality evaluation of gradient oriented compressed coded aperture imaging", Proc. SPIE 12065, AOPC 2021: Optical Sensing and Imaging Technology, 1206540 (29 December 2021); https://doi.org/10.1117/12.2606503

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KEYWORDS

Image quality

Reconstruction algorithms

Image processing

Chemical species

Compressed sensing

Detection theory

Image compression

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