Image Enhancement Using Particle Swarm Optimization
نویسندگان
چکیده
Applications of the Particle Swarm Optimization (PSO) to solve image processing problem with a reference to a new automatic enhancement technique based on real-coded particle swarms is proposed in this paper. The enhancement process is a non-linear optimization problem with several constraints. The objective of the proposed PSO is to maximize an objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The feasibility of the proposed method is demonstrated and compared with Genetic Algorithms (GAs) based image enhancement technique. The obtained results indicate that the proposed PSO yields better results in terms of both the maximization of the number of pixels in the edges and the adopted objective evaluation. Computational time is also relatively small in the PSO case compared to the GA case.
منابع مشابه
Niche Particle Swarm Optimization Combined with Chaotic Mutation Application in Image Enhancement
A niche chaotic mutation particle swarm optimization (NCPSO) algorithm is proposed to overcome the problem of loss details of images, the contrast is not obvious and poor adaptability in traditional image enhancement methods. In this algorithm, niching methods and elimination strategy are introduced to improve the global optimization ability. Mutative scale chaos mutation algorithm has refined ...
متن کاملRecent Trends and Techniques in Image Segmentation using Particle Swarm Optimization-a Survey
Particle swarm optimization is the nature inspired computational search and optimization approach which was developed on the basis of behaviour of swarm. Recently each and every field of research is utilizing the properties of PSO. One of the popular field of research is image segmentation which is also fastest growing field. Taking the advantages of combining PSO with different image segmentat...
متن کاملImage Contrast Enhancement Approach Using Differential Evolution and Particle Swarm Optimization
Differential Evolution (DE) algorithm represent an adaptive search process for solving engineering and machine learning optimization problems. This paper presents an attempt to demonstrate its adaptability and effectiveness for searching global optimal solutions to enhance the contrast and detail in a gray scale image. In this paper contrast enhancement of an image is performed by gray level mo...
متن کاملAn Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm
Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function a...
متن کاملImage Enhancement Techniques Using Particle Swarm Optimization Technique
The image quality enhancement process is considered as one of the basic requirement for high-level image processing techniques that demand good quality in images. High-level image processing techniques include feature extraction, morphological processing, pattern recognition, automation engineering, and many more. Many classical enhancement methods are available for enhancing the quality of ima...
متن کاملA New Shuffled Sub-swarm Particle Swarm Optimization Algorithm for Speech Enhancement
In this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. The new method is a hybrid optimization algorithm, which employs the combination of the conventional θ-PSO and the shuffled sub-swarms particle optimization (SSPSO) technique. It is known that the θ-PSO algorithm has better optimization performance than standard PSO al...
متن کامل