Compression imaging based on Fourier transform optical system

Jinfeng Lv; Huaici Zhao; Chunyang Zhao

doi:10.1117/12.2073026

24 November 2014 Compression imaging based on Fourier transform optical system

Jinfeng Lv, Huaici Zhao, Chunyang Zhao

Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 93012S (2014) https://doi.org/10.1117/12.2073026
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China

Abstract

Shannon / Nyquist sampling theorem indicates that during the sampling process the minimum sample rate must be more than the double of the band of the signal so that we can achieve images without distortion. High-frequency sampling leads to mass data and results in high cost of storage and transmission procedure. Compressed sensing indicates that we can sample data at far below the Nyquist frequency when the signals are sparse or can be represented as sparse on some orthogonal basis, and the signals can be recovered without distortion after some certain recovery algorithms. By this means the cost of storage and transmission can be reduced significantly. Unlike conventional optical imaging process, this paper presents a new imaging method using a Fourier transform lens system, which enables single-exposure and single-aperture compressed imaging. First, the Fourier transformation of image signals is accomplished after they pass through a Fourier transform optical system. Second, sparse sample data can be obtained after the spectrum signals pass the sensor array. The process mentioned above can be interpreted as that using a Fourier matrix and a sparse matrix to complete the measurement of the image signals. Third, we make use of fast iterative threshold recovery algorithm to compute the sampling values and obtain the target image signals. Compared with the conventional imaging methods, in the case of ensuring the image quality, our method can significantly reduce the number of samples, thus greatly reduce the data redundancy. Simulation results indicate that the imaging method proposed can be prospective.

Citation Download Citation

Jinfeng Lv, Huaici Zhao, and Chunyang Zhao "Compression imaging based on Fourier transform optical system", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93012S (24 November 2014); https://doi.org/10.1117/12.2073026

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KEYWORDS

Fourier transforms

Imaging systems

Image processing

Cameras

Compressed sensing

Signal processing

Image quality

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