A new illumination estimation method based on local gradient for retinex

Park, Se-Kyung; Kim, Byung‐Sung; Chung, Eui-Yoon; Lee, Kwae-Hi

doi:10.1109/isie.2009.5218886

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2014

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“…To obtain a proper blurring effect, we should carefully determine the filter window size according to image sizes. One of the thumb rules suggests 1%∼5% of the image size for the Gaussian half-width σ and two times of σ for the filter window size [25]. If we take 3% of σ for a 512 × 512 resolution image, the filter window size becomes about 30.…”

Section: Resultsmentioning

confidence: 99%

Two-way partitioning of a recursive Gaussian filter in CUDA

Lee

Choe

2014

J Image Video Proc

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Recursive Gaussian filters are more efficient than basic Gaussian filters when its filter window size is large. Since the computation of a point should start after the computation of its neighborhood points, recursive Gaussian filters are line oriented. Thus, the degree of parallelism is restricted by the length of the data image. In order to increase the parallelism of recursive Gaussian filters, we propose a two-way partitioned recursive Gaussian filter. The proposed filter partitions a line into two lines and a point, which is used for Gaussian blur effect across the two lines. This partition increases the parallelism because the filter is applied to the two blocks in parallel. Experimental results show that the process time of the proposed filter is half compared to the time of an one-way parallel recursive Gaussian filter while the peak signal-to-noise ratio is maintained within an acceptable rate of 26 to 33 dB.

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Section: Resultsmentioning

confidence: 99%