Ms. Fang Zhao Profile

Fang Zhao

at Shenyang Ligong Univ

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Proceedings Article | 25 May 2023 Paper

An improved Criminisi de-highlighting algorithm

Fang Zhao, Shiqing Ren

Proceedings Volume 12636, 126365B (2023) https://doi.org/10.1117/12.2675205

KEYWORDS: Detection and tracking algorithms, Visualization, RGB color model, Histograms, Reflection, Light sources and illumination, Image processing, Floods, Data modeling, Signal to noise ratio

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In daily production and life, high-quality images are often pursued. But the reality is always the opposite, and highlighting is one of the reasons why the image quality is not so good. Therefore, this paper studies the effective removal of highlight phenomenon in a single image. First of all, significant detection algorithm based on YCrCb color space using the vision algorithm (LC) get significant figure of specular image, and then will meet the requirements of significant value as the initial seed points of region growing algorithm, and according to the rule of its growth will highlight areas detected, then uses the open operation and flood water filling algorithm will detect the highlight areas are optimized; Then, the optimized highlight region detection map is used as the mask image criminisi algorithm, and criminisi algorithm is improved from three aspects: priority calculation, matching criteria and updated confidence. Finally, based on the improved criminisi algorithm, criminisi can effectively remove the detected highlight area and obtain the original information of the image covered by the highlight. The experimental results show that the method proposed in this paper can obtain the details of the highlight region, remove the highlight well, and make the image clearer after the removal of the highlight.

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