Full HD Low-Light Video Real-Time Enhancement for General-Purpose CPUs

Aiming at the poor observation effect of video images due to insufficient light source or unbalanced illumination, and the difficulty of real-time performance of existing algorithms, a brightness equalization algorithm and its parallel optimization method based on layered thinking were proposed. Firstly, the bright and dark areas are divided in the HSV color space. Then the brightness adaptive gain modulation is performed on the low-illumination area. Thirdly, the generated brightness-gain mapping table is applied to the RGB space to achieve low-illumination video image enhancement. For real-time requirements, the 256-level grayscale is mapped to a two-dimensional Luminance Gain Lookup Table (2D-LGLUT) to solve the problem of repeated calculation per frame, and the Intel Advanced Vector Extensions (A VX) instruction set is applied. It realizes efficient and fast processing of 256-bit pixels in a single instruction. The experimental results show that the adopted method achieves the real-time <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(\geq 7\text{lf}/\mathrm{s})$</tex> processing target of full High Definition (HD, 1920<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sup>l080) video images while ensuring the brightness equalization effect.