Low-illumination color video enhancement method by using space-time illumination map

Abstract

The invention discloses a low-illumination color video enhancement method by using a space-time illumination map. Firstly the initial space illumination map of the video frame is calculated, the timesimilarity illuminance map of the current video frame is calculated by using the initial space illuminance map of the current video frame and previous k video frames, the initial space illumination map and the time similarity illumination map are utilized to construct the structure weight matrix of the current video frame, the cost minimization model of the optimal illumination map estimation is constructed by using the initial space illumination map, the time similarity illumination map and the structure weight matrix and the solution is obtained as the optimal illumination map of the currentvideo frame, and finally the gamma correction is performed on the optimal illumination map and the enhanced current video frame is obtained by using the corrected illumination map. When all the videoframes are processed, all the enhanced video frames are combined to output the color video. The method can effectively enhance the illuminance of the low-illumination color video while maintaining the main structure in the video frame and makes the enhanced video have coherent illuminance.

Description

technical field [0001] The invention relates to a low-illuminance color video enhancement method using a spatiotemporal illumination map, which belongs to an image enhancement technology. Background technique [0002] In the case of insufficient natural light, the videos shot by people often have low illumination and poor visual effects, which cannot truly reflect the details of objects in the target scene. For some vision-based applications, such as target detection, target Tracking, etc., have caused great inconvenience. [0003] The methods for enhancing low-light images or videos can be roughly divided into two categories, one is the method based on histogram, and the other is the method based on Retinex theory. The histogram-based method improves the resulting image or video frame by adjusting the histogram distribution of the image or video frame. However, it does not solve the problem of illumination enhancement from the essence of image illumination, but only improv...

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Problems solved by technology

A fusion-based enhancing method for weakly illuminated images, vol.129, no. 2016, pp.82-96, 2016), three different illumination maps are generated in three ways, and then weighted and fused into an enhanced illumination map. However, this method does not consider the structural information in the image, which will cause some textured areas lighting distortion

The Chinese patent "A Low Illumination Video Image Enhancement Method" [201310639998.5] performs intra-frame enhancement on the illumination of each frame of image, and performs inter-frame enhancement on the previous frame enhancement result as the standard frame of the next frame image. However, this method also does not take into account the structural information in the video frame

Chinese patent "A Real-time Enhancement Method for Low-Illumination Video Based on Bright Channel" [201510181696.7] obtains an illumination factor by calculating the mean value of low-illuminance video frames and the value of the bright channel, and the simple relationship between the illumination factor and the pixel intensity of the video frame The algebraic operation of the method is used to obtain the enhanced video frame. This method is fast and can meet the requirements of real-time processing, but it does not use the inter-frame information of the video.

Xiaojie Guo et al proposed a low-light image enhancement method (Xiaojie Guo, Yu Li, Haibin Ling, LIME: Low-light image enhancement via illumination map estimation, IEEE Transactions on Image Processing, vol.26, no.2, pp.982- 993, 2017), by estimating the illuminance map to achieve the purpose of enhancing the image illuminance, this method takes into account the spatial structure information inside the image, and can estimate a spatially segmented and smooth illuminance map, but it is not suitable for processing low-level images that contain temporal information. Illumination video

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