KEYWORDS: Point spread functions, Probability theory, Signal to noise ratio, Deconvolution, Evolutionary algorithms, Image restoration, Detection and tracking algorithms, Image analysis, Image processing, Statistical analysis
This paper proposes an improved blind deconvolution algorithm, which adopts maximum likelihood method to find the
most similar estimation of the PSF and object with Poisson-based probability model. The algorithm integrates Cauchy
probability distribution model into the estimation of the PSF under the condition of low SNR, uses the characteristic of
short-exposure image sequence that the adjacent images have similar PSF to get restored image with frames as few as
possible. The experimental results show that this method is robust with high ability of resisting noise in the restoration of
turbulence-degraded images.
KEYWORDS: Digital signal processing, Field programmable gate arrays, Image processing, Parallel processing, Signal processing, Data processing, Deconvolution, Detection and tracking algorithms, Image restoration, Point spread functions
In this paper, we present a co-design method for parallel image processing accelerator based on DSP and FPGA. DSP is
used as application and operation subsystem to execute the complex operations, and in which the algorithms are
resolving into commands. FPGA is used as co-processing subsystem for regular data-parallel processing, and operation
commands and image data are transmitted to FPGA for processing acceleration. A series of experiments have been
carried out, and up to a half or three quarter time is saved which supports that the proposed accelerator will consume less
time and get better performance than the traditional systems.
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