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Local visual adaptation model-based real image reproduction method

An adaptive model and local technology, applied in the field of image processing, can solve the problems of excessive gain and loss in bright areas, and achieve the effect of true color, high realization efficiency and low calculation amount.

Inactive Publication Date: 2011-11-02
BEIJING INSTITUTE OF TECHNOLOGYGY
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AI Technical Summary

Problems solved by technology

[0012] The problem that often occurs in practical applications is that it is easy to achieve effective enhancement of dark areas in images with both bright and dark areas, but often the gain in bright areas is too large, resulting in loss of texture and detail information; the difference between image color richness and image clarity There are also trade-offs between

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  • Local visual adaptation model-based real image reproduction method
  • Local visual adaptation model-based real image reproduction method
  • Local visual adaptation model-based real image reproduction method

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Embodiment Construction

[0042] 1. Fixed parameter mode

[0043]This mode is implemented with fixed brightness and contrast control factors, which can be determined experimentally or empirically for different scenes in the image. Among them, if a smaller brightness control factor c is selected, the overall brightness of the image will increase significantly, especially the overexposure phenomenon in bright areas; otherwise, the brightness will decrease, and it will be difficult to distinguish image information in dark areas. When the contrast control factor α is small, the dynamic compression ability is strong, especially the details of the dark area are greatly enhanced, but the color expressiveness is poor; on the contrary, the dynamic range compression ability is poor, and the color fidelity is good. The contradiction of parameter selection will lead to the loss of texture or color information in different brightness regions in the image. According to the subjective test results, Figure 4 In α=1...

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Abstract

The invention relates to a local visual adaptation model-based real image reproduction method, which belongs to the field of image processing. The method comprises: firstly, obtaining a pixel value of an object to be processed by inputting an image; secondly, computing a local background brightness of each pixel neighborhood according to the pixel value; thirdly, designing a contrast and a brightness control factor according to the local background brightness; fourthly, substituting the contrast and the brightness control factor a and c into the local visual adaptation model so as to obtain anormalized output result; and finally, performing post-processing on the normalized output result to obtain a final image reproduction result. The method can effectively realize compression or adjustment in a dynamic range, maintains image details to avoid a false image, and has certain colour constancy, low complexity and good practicability.

Description

field of invention [0001] The invention relates to the field of image processing, in particular to high dynamic range image compression or image dynamic range adjustment and color constancy maintenance technology in specific applications of image processing. technical background [0002] Natural scenes present rich colors and a wide range of brightness in front of human eyes. For example, the average brightness at night is about 10 -6 cd / m 2 , even up to 10 under sunlight conditions 8 cd / m 2 , and the brightness in a single scene may span several orders of magnitude. The human visual system can adapt to a wide range of light intensities, from night vision thresholds to strong flashes of about 10 10 order of magnitude. Normally, the human eye can distinguish 10 4 Detail information in the order of magnitude range, and only halo around the flash and loss of detail. Human vision has such a high dynamic range, which is unmatched by current general-purpose display devices....

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04N9/64H04N1/56
Inventor 倪国强肖蔓君陈思颖
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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