OPTIMAL LEVEL OF DECOMPOSITION OF STATIONARY WAVELET TRANSFORM FOR REGION LEVEL FUSION OF MULTI-FOCUSED IMAGES
Journal: ICTACT Journal on Image and Video Processing (IJIVP) (Vol.1, No. 2)Publication Date: 2010-11-01
Authors : K. Kannan; S. Arumuga Perumala;
Page : 76-79
Keywords : Image Fusion; Region Level Fusion; Discrete Wavelet Transform; Stationary Wavelet Transform;
Abstract
In machine vision, due to the limited depth-of-focus of optical lenses in CCD devices, it is not possible to have a single image that contains all the information of objects in the image. To achieve this, image fusion is required which is usually refers to the process of combining two or more different images, each containing different features into a new single image retaining important features from each and every image with extended information content. The approaches to image fusion can be classified into two namely Spatial Fusion and Transform fusion. The most commonly used transform for image fusion at multi scale is Discrete Wavelet Transform since it minimizes structural distortions. But, wavelet transform suffers from lack of shift invariance and this disadvantage is overcome by Stationary Wavelet Transform. This paper describes the optimum level of decomposition of Stationary Wavelet Transform for region based fusion of multi focused images in terms of various performance measures.
Other Latest Articles
- FAST DISCRETE CURVELET TRANSFORM BASED ANISOTROPIC FEATURE EXTRACTION FOR IRIS RECOGNITION
- A SWITCHING ALGORITHM USING MODIFIED SELECTION SORT FOR THE REDUCTION OF IMPULSE NOISE
- ROBUSTNESS OF A FACE-RECOGNITION TECHNIQUE BASED ON SUPPORT VECTOR MACHINES
- IMPROVED HYBRID SEGMENTATION OF BRAIN MRI TISSUE AND TUMOR USING STATISTICAL FEATURES
- CODEVECTOR MODELING USING LOCAL POLYNOMIAL REGRESSION FOR VECTOR QUANTIZATION BASED IMAGE COMPRESSION
Last modified: 2013-12-03 19:57:29