A high dynamic range image tone mapping method with detail enhancement and brightness self-adaptation

Abstract

The invention discloses a high dynamic range image tone mapping method with detail enhancement and brightness self-adaptation. The invention enhances the global detail of the input HDR image brightness gray-scale image, calculates the logarithm of the HDR image brightness gray-scale image after the detail enhancement, and utilizes logarithmic conversion to initially compress the brightness in theoriginal scene. Then the brightness histogram is statistically analyzed, and the average value and standard deviation are calculated, and the histogram is clipped and compensated in segments. Then theaverage brightness and the standard deviation of the mapped middle low dynamic range image are calculated by the brightness and standard deviation estimation model, so as to solve the global mappingcurve of the brightness histogram from the HDR image to the middle LDR image, wherein the maximum entropy brightness estimation method adaptively selects the optimal output brightness of the middle LDR image. Then, the brightness of the LDR image is obtained by local detail enhancement mapping to the brightness of the intermediate LDR image which is too dark or too bright. At last, that color of the HDR image is map to the color of the output LDR image, and the color space is merged to obtain the output LDR image. The invention can map the HDR image to the LDR image, the output LDR image brightness is adaptive, the detail is enhanced, and the subjective effect is harmonious.

Description

technical field [0001] The present invention designs a tone mapping method of a high dynamic range image (referred to as HDR image) with detail enhancement and brightness self-adaptation. The average brightness and standard deviation of the middle low dynamic range image (LDR image for short), so as to obtain the high dynamic range image tone mapping method of the output LDR image with detail enhancement and brightness adaptation. Background technique [0002] The current CMOS sensor has been able to collect images of real scenes with a high dynamic range of 170dB, thus posing new challenges to traditional image storage, transmission, processing, reproduction and other technologies. Therefore, there are various methods for compressing the dynamic range of the collected HDR images, so as to solve the problem of the mismatch between the dynamic range of the real scene and storage, transmission, processing, reproduction and other technologies. This way of compressing high dyna...

AI Technical Summary

Problems solved by technology

However, the current method of tone mapping relies too much on the adjustment of related parameters,

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