Endoscopic image highlight removal method based on non-convex low-rank matrix decomposition

Abstract

The invention provides an endoscopic image highlight removal method based on non-convex low-rank matrix factorization, which comprises the following steps: an absolute highlight detection stage: statistical attributes of an image on saturation and intensity values are calculated, an adaptive threshold is generated, a double-threshold segmentation algorithm is executed, absolute highlight pixels are detected, and an absolute highlight image is generated; a non-convex low-rank matrix decomposition stage: non-convex low-rank matrix decomposition is executed on each image, gradient information isintroduced in the iterative optimization process with the position information of absolute highlight pixels as priori knowledge, and a low-rank image and a sparse image are calculated; an image fusionand reconstruction stage: a finer highlight image is generated, morphological operation and linear filtering operation are executed, a self-attenuation weight image is generated, pixel-level fusion of a low-rank image and an original endoscope image is executed, and an endoscope image without highlight is generated; image blocking and integration: an original image with a large size is divided into a plurality of sub-images by adopting an image blocking technology, and multi-task parallel computing is realized by adopting a multi-thread technology.

Description

technical field [0001] The invention relates to a method for removing highlights of endoscopic images based on non-convex low-rank matrix decomposition. Background technique [0002] As a commonly used medical device in clinical medicine, medical endoscopes can be seen almost everywhere in lesion detection, clinical diagnosis and surgery. It provides information on the internal conditions of the human body to doctors in the form of images, helping doctors to observe the human body more clearly and carefully. Internal organization status. Due to the humid environment and smooth mucosal surface inside the human body, the endoscope will introduce noise attributes such as highlights and foggy while sampling the tissue surface information, thereby degrading the quality of endoscopic images. As the most common type of noise in endoscopic images, highlight removal is very important. [0003] Previous research on highlight removal mainly includes four categories. The first categor...

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Problems solved by technology

[0005] The technical problem solved by the present invention is to overcome the problem of difficult parameter selection in the low-rank decomposition algorithm, and provide a method for removing highlights of endoscopic images based on non-convex lo

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