Restoration of color-quantized images is rarely addressed in the literature, especially when the images are color-quantized with half-toning. Many existing restoration algorithms are inadequate to deal with this problem because they were proposed for restoring noisy blurred images only. In this chapter, a restoration algorithm based on Particle Swarm Optimization with multi-wavelet mutation (MWPSO) is proposed to solve the problem. This algorithm makes good use of the available color palette and the mechanism of a half-toning process to derive useful a priori information for the restoration. Simulation results show that it can improve the quality of a half-toned color-quantized image remarkably in terms of both signal-to-noise ratio improvement and convergence rate. The subjective quality of the restored images can also be improved.
|Title of host publication||Computational Intelligence and its Applications|
|Subtitle of host publication||Evolutionary Computation, Fuzzy Logic, Neural Network and Support Vector Machine Techniques|
|Publisher||Imperial College Press|
|Number of pages||19|
|Publication status||Published - 1 Jan 2012|
ASJC Scopus subject areas
- Computer Science(all)