Single-exposure high-dynamic range image generation method adapted to medical image

Abstract

The invention discloses a single-exposure high-dynamic range image generation method adapted to a medical image. The method comprises the steps that 1) images of different exposure are generated on the basis of reverse tone mapping, and a reverse tone mapping function is modeled; 2) according to a pseudo-exposure HDR image generated in the first step, a weight graph of the image is obtained on the basis of a pyramid decomposed multi-exposure image fusion algorithm; 3) Laplacian pyramid decomposition is carried out on a sequence of N multi-exposure images, Gaussian pyramid decomposition is carried out on N weight graphs, and images and weight graphs of different resolutions are obtained, and a fusion formula is obtained; and finally, Laplacian inverse transformation is carried out on a pyramid L{R}l to obtain a fused image R. Thus, an HDR image synthesized by input image is obtained. Compared with an original image, the synthesized HDR image is higher in contrast, more distinct in colors, and more reinforced in details; a fusion algorithm is low in computational complexity; and high dynamic range image generation can be realized in real time.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a single-exposure high dynamic range image generation method adapted to medical images. Background technique [0002] Medical imaging refers to the technology and processing process of obtaining internal tissue images of the human body or a certain part of the human body in a non-invasive manner for medical treatment or medical research. It includes the following two relatively independent research directions: medical imaging system and medical image processing. The former refers to the process of image formation, including the research on imaging mechanism, imaging equipment, imaging system analysis and other issues; the latter refers to the further processing of the obtained image, the purpose of which is to restore the original image that is not clear enough , or to highlight some feature information in the image, or to classify the pattern of the image and s...

AI Technical Summary

Problems solved by technology

[0004] At present, there have been many researches on high dynamic range image generation methods. For example, Mann and Picard first used multiple images with different exposure times to generate HDR images. Goshtasby et al. proposed an image fusion algorithm based on optimal blocks, but it is easy to produce Block effect, Mertens et al proposed an image fusion algorithm based on Laplacian pyramid, Li et al proposed an image fusion algorithm based on discrete wavelet

However, the above methods all use multiple pictures with different exposures, and the acquisition of pictures is more complicated.

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