On using an associative memory for improving digital color images: color characterization, enhancement, and color balancing

Actual observed scenes usually produce a wide dynamic range. Currently available visual systems use low dynamic range light detector that provide only 8 bits of brightness information at each pixel. This greatly limits what visual systems can do for surveillance applications such as face detection and face recognition. A color image enhancement procedure based on the concept of color characterization, enhancement, and color balancing is proposed in this paper. The enhancement technique directly operates on pixels using a hyperbolic tangent function to increase the dynamic range of the pixel. The global and local statistics of the image is used to control the curvature of the hyperbolic tangent function. The color characterization and color balancing processes are based on a new nonlinear line attractor network to create a color manifold to restore the relationship of red, green, and blue components of the pixels. The proposed enhancement approach greatly improves the dynamic range compression and color rendition of an image.