Adaptive image enhancement method based on interesting area

Abstract

The invention provides an adaptive image enhancement method based on an interesting area, which comprises: reading a present frame image and determining if a macro-block of the frame image is the interesting area; if the macro-block is the interesting area, then calculating every pixel point in the interesting area using ASAD algorithm to obtain ASAD values of all pixel points in the interesting area; getting an ASAD grey-scale map through the ASAD values; carrying out an enhanced treatment to the ASAD grey-scale map to obtain an adaptive threshold; comparing the adaptive threshold with ASAD values to get an ASAD mask artwork; carrying out Gauss high pass filtering for the corresponding mark point in the interesting area according to the ASAD mask artwork to obtain an interesting area with an enhanced adaptation; and carrying out a degraded treatment to a boundary of the interesting area and the disinteresting area. The method in the invention enhances high frequency details properly in different frame images to obtain an optimum enhanced effect.

Description

technical field [0001] The invention relates to the field of multimedia signal processing, in particular to an adaptive image enhancement method based on a region of interest. Background technique [0002] Although the existing video coding technology (such as H.264 / AVC) can achieve a high compression ratio and obtain relatively good compression efficiency, when it is applied to mobile video communication, desktop real-time video and other low-bit-rate applications When in the scene, the subjective quality of the image / video is often reduced due to the low bit rate requirement, especially in the face area where the human eye is more sensitive, there will be blurring, squares and other effects, which seriously affect the video quality. [0003] In order to improve and enhance the subjective image / video quality in low bit rate or bandwidth-limited applications, video quality enhancement preprocessing is a general and effective technical means. This method often combines image...

AI Technical Summary

Problems solved by technology

[0004] Although the above method has a good effect on single image processing, when it is applied to video subjective quality enhancement, there will be the following problems: the video is composed of different frame images that change continuously, and the region of interest in each frame image needs to be enhanced. The strengths are all different. When the above method continuously processes different frame images, some frame edge enhancements will be excessive and some frame edge enhancements will be too weak, so that the enhancement intensity of different images cannot be adaptively adjusted.

Images