Enhancing the output of spatial color algorithms

Development and implementation of spatial color algorithms has been an active field of research in image processing for the last few decades. A number of investigations have been carried out so far in mimicking the properties of the human visual system (HVS). Various algorithms and models have been developed, but they produce more or less neutral output. Some applications demand the preservation of appearance of the original image along with the enhancement performed by these models. It is our attempt in this paper to present a number of techniques that are designed to satisfy the requirements of those applications. Our techniques work in two general stages. In the first stage, properties of the original image are extracted and stored. In the second stage, the resulting images from the image enhancement models are processed with those properties. Most of these techniques perform quite well for different categories of images. We combine different approaches such as gamma, scaling, linear, scaling and clipping to preserve properties like color cast, maximum and minimum channel value etc. Our methods have been extended for Low-key and High-key images as well.