A novel slime mold algorithm for grayscale and color image contrast enhancement

Abstract

Image enhancement is a key step in image pre-processing. To address the problem of low quality and visual effect of images under low illumination conditions, this paper proposes an image enhancement method with hyperbolic oscillation factor and quadratic interpolation of slime mold algorithm (SSMA) in non-complete beta function dynamically looking to adjust the grayscale curve. The new strategy mainly proposes three different improvement strategies for the problem that the classical slime mold algorithm has low convergence accuracy and can easily fall into local optimum. Experimenting the proposed SSMA with other conventional and latest algorithms on the CEC2017 benchmark function and low-illumination standard dataset. The experimental results show that the convergence accuracy and convergence speed of SSMA are better than other algorithms. The proposed SSMA-optimized image enhancement algorithm effectively enhances the image brightness while preserving more details of the image, which is significantly better than other algorithms for image enhancement.