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Multiscale Retinex image sharpening algorithm based on bounded operation

A multi-scale and sharpening technology, applied in image enhancement, image data processing, computing and other directions, can solve the problem of halo phenomenon, and achieve to overcome the halo artifact phenomenon and over-enhancement phenomenon, strong anti-noise ability, image Contrast-enhancing effect

Inactive Publication Date: 2015-04-29
CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
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Problems solved by technology

[0004] The present invention provides a multi-scale Retinex image clearing algorithm based on bounded operations in order to solve the limitations of the existing image enhancement algorithm in realizing image clearing, and the halo phenomenon will occur in areas with strong illuminance changes.

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  • Multiscale Retinex image sharpening algorithm based on bounded operation
  • Multiscale Retinex image sharpening algorithm based on bounded operation
  • Multiscale Retinex image sharpening algorithm based on bounded operation

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specific Embodiment approach 1

[0026] Specific implementation mode 1. Combination figure 1 Description of the present embodiment, based on the multi-scale Retinex image sharpening algorithm of bounded operation, according to the proposed bounded generalized logarithmic ratio (GLR, General Log-Radio) operation model, the addition in the GLR model replaces the pairing in the Retinex algorithm The logarithmic transformation is performed on the image; the self-adaptive guiding filter kernel function of different scales is used to separate the high and low frequency information, and the irradiation images of different scales are obtained;

[0027] Then the illumination component is removed by the subtraction of the GLR model to segment the reflection components of different scales from the original image;

[0028] Using the four-direction Sobel gradient image, the multiplication and addition of the bounded GLR model is used instead of the traditional operation to fuse the effective information of different scale...

specific Embodiment approach 2

[0046] Specific embodiment two, combine Figure 1 to Figure 8 Describe this embodiment, based on the multi-scale Retinex image sharpening algorithm with bounded operation, this embodiment uses the GLR model addition of bounded operation, and selects the transformation factor a 1 , perform a logarithmic transformation on the original image II(x,y) to obtain ii(x,y), and convert it to the logarithmic domain suitable for the visual perception of brightness; perform guided filtering of different scales on the original image, and select different transformations factor, for the guided filtered image I' i (x, y) uses GLR model addition to perform logarithmic transformation, and obtains the illumination component l' of the image in the logarithmic domain i (x, y); and then remove the illumination component by the subtraction of the GLR model to convert the reflection component r' of images of different scales i (x, y) is segmented from the original image; the human eye is sensitive...

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Abstract

The invention discloses to a multiscale Retinex image sharpening algorithm based on bounded operation, relates to the technical field of digital image processing and solves the problems that existing image intensification algorithm has limitation in realizing image sharpening and generates a halo formation in a region with relatively strong change of intensity of illumination and the like. The algorithm comprises the following steps: according to a bounded generalized log ratio operating model put forward, replacing logarithm transformation in Retinex algorithm by addition in a GLR model to carrying out logarithm-like transformation on an image; separating high and low frequency information by adopting a self-adaptive guide filter kernel function of different scales to obtain illumination images of different scales; then removing illumination components by using subtraction of the GLR model to partition reflective components of different scales from an original image; fusing effective information of different scales by using multiplication and addition of the bounded GLR model for replacing conventional algorithm through a four-way Sobel gradient image to obtain a final multiscale reflective component image, namely the final sharpened image.

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to a multi-scale Retinex image sharpening algorithm based on bounded operations. Background technique [0002] At present, digital image processing technology has been widely used in military, national defense, medical, monitoring and other fields, but due to the influence of low illumination, uneven illumination, fog and other harsh environments in the imaging process, image degradation, such as details Unclear, poor contrast, low signal-to-noise ratio, etc., so there is an urgent need for image clarity processing. Image sharpening can improve image contrast and improve visual effects to facilitate subsequent analysis of images, such as image segmentation, target recognition, and target tracking. [0003] There are many current image enhancement methods, mainly including: histogram equalization, homomorphic filtering, and Retinex algorithm, etc., but each algorith...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 毕国玲赵建续志军孙强
Owner CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
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