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Image fusion is the process of combining two or more images into a single image while retaining the important features of each image. Multiple image fusion is an important technique used in military, remote sensing and medical applications. This paper presents a new method of image fusion for impulse noise removal in digital images. The images are captured by five sensors and undergo filtering by five different filtering algorithms. These five de-noised images from five different filters are combined into a single image to obtain a high quality image compared to individually de-noised image. The performance of the Image Fusion is evaluated by using a reference image quality metric, Structural similarity Index (SSIM), to estimate how well the important information in the de-noised images is represented by the fused image. Experimental results show that the fused image has more quality than other filtered images.
Dr.J.Harikiran. 1970. \u201cA New Method of Image Fusion Technique for Impulse Noise Removal in Digital Images\u201d. Unknown Journal GJCST Volume 11 (GJCST Volume 11 Issue 7): .
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Total Score: 109
Country: India
Subject: Uncategorized
Authors: Dr.J.Harikiran ,B.Saichandana, K.Keerthi, D.Anish (PhD/Dr. count: 1)
View Count (all-time): 91
Total Views (Real + Logic): 20906
Total Downloads (simulated): 11027
Publish Date: 1970 01, Thu
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Image fusion is the process of combining two or more images into a single image while retaining the important features of each image. Multiple image fusion is an important technique used in military, remote sensing and medical applications. This paper presents a new method of image fusion for impulse noise removal in digital images. The images are captured by five sensors and undergo filtering by five different filtering algorithms. These five de-noised images from five different filters are combined into a single image to obtain a high quality image compared to individually de-noised image. The performance of the Image Fusion is evaluated by using a reference image quality metric, Structural similarity Index (SSIM), to estimate how well the important information in the de-noised images is represented by the fused image. Experimental results show that the fused image has more quality than other filtered images.
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