Soft proofing of images using Bacteria foraging optimization of color gamuts
Nayan Malpani, Roshan Jain, Saurabh Maheshwari · 2016
Soft proofing is the method to visualize how an image will look like on the electronic display after printing with a particular printer on a specific paper. It is required to save unnecessary frequent prints and save paper thus money. The display on which a particular image is presented may have support for less number of colors than the original image has. We treat soft proofing problem as color quantization. Use of Swarm Intelligence methods like Ant Colony Optimization and Bacteria Foraging Optimization have been very efficient and produce good resultant quantized images. The problem with these methods is their complexity of implementation. So the main target is to reduce the complexity of the color image quantization. This paper proposes an efficient technique for soft proofing of images using bacteria image foraging optimization where frequently present colors in histogram will be selected for an image. The main aim is to minimize and optimize the total number of available colors in an original image according to the target gamut. Later this method is compared with the older strategies where each pixel of the image is compared to every other pixel to check whether it is part of same color cluster. The method used in this paper is very less complex in performance yet optimal in transform and quantization in comparison to other color image quantization based on Bacteria Foraging Optimization. The results of processing time, histogram comparison and number of colors in resultant images are compared with previous works. This is first ever attempt of soft proofing of images using bacteria foraging optimization and it also ensures that the size of original and final image does not changes even after low resolution printing.