Tencent Technology (shenzhen) Company Limited

Tencent Technology Company Limited

Benchao Li

Feng Li

Yi Liu

Chenghao Liu

Juanhui Tu

Tong Ai

Qifeng Chen

An image processing method includes: determining a brightness value of an image; and enhancing a brightness of the image when the brightness value of the image is less than an image brightness threshold. Enhancing the brightness of the image includes: determining each pixel of the image as a target pixel; determining a brightness enhancement value of the target pixel based on the brightness value of the image, an initial brightness value of the target pixel, and initial brightness values of neighboring pixels of the target pixel; and using the brightness enhancement value as an enhanced brightness value of the target pixel.

Image processing method and apparatus, computing device, and storage medium

An image processing method includes: obtaining a target image; performing blurring processing on an original image of a specified channel of channels of the target image to obtain a first blurred image; performing high pass processing on the original image of the specified channel and the first blurred image to obtain a high pass image; obtaining, for a channel, a second blurred image corresponding to the channel based on an original image of the channel and the high pass image; and obtaining a processed image corresponding to the target image based on the second blurred image of the channel and the high pass image.

Image processing method and apparatus, video processing method and apparatus, electronic device, and storage medium

A video denoising method includes: performing spatial filtering on pixels of a target image in a video to be processed to obtain a first image, the spatial filtering being used for eliminating dependencies between the pixels of the target image; performing, according to a frame difference between the first image and a first denoised image, temporal filtering on the pixels of the target image in parallel to obtain a second image, the first denoised image being an denoised image that corresponds to a preceding frame of the target image; predicting first gain coefficients corresponding to pixels of the second image in a second denoised image according to second gain coefficients corresponding to the pixels of the target image in the first denoised image; and fusing the first image and the second image according to the first gain coefficients to obtain the second denoised image that corresponds to the target image.

Video denoising method and apparatus, terminal, and storage medium

Growing community of inventors

Shenzhen, China

Benchao Li