A Multi-Scale Gabor Filter-Based Method for Enhancing Video Images in Distance Education

Due to the limited network bandwidth and low-quality end-user devices, the images in distance education videos are transferred in low resolution. It results in low clarity, which badly affects video visibility and leads to poor learning effects. Therefore, a video-enhancing mechanism is required in distance education to ensure quality visualization. The quality is enhanced using a multi-scale Gabor filter, where a color image in the video is converted from the RGB space to the HSI space. A grey-level objective optimization function is constructed to attain a grey-scale image by the gradient conjugate solution method. The attained grey-scale image is used as the basis to obtain the grey-level change information of an image in different directions by using the multi-scale Gabor filter. The image texture is completed and enhanced by using the fractional order differential mask. The local information of the grey-scale images in educational videos is selected and a video image is obtained after the construction of the adaptive mask operator. The experimental results show that the proposed method can effectively grey-scale the images in distance education videos, which improves the sharpness and contrast, and effectively extract the local information. Moreover, the difference between the actual pixels is small, where the maximum difference is 144 and the minimum difference is 55, which shows the extraction results are more accurate.