High PSNR based Image Fusion by Weighted Average Brovery Transform Method

Taxak, Nidhi; Singhal, Sachin

doi:10.1109/devic.2019.8783400

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…Recent trends to apply hybrid fusion techniques like hybridization weighted average/Brovery [231], HIS/PCA [285,286], Laplacian/maximum likelihood [265], IHS/WT [287], contourlet/PCA [288], Laplacian/DCT [266], Bloc replacement/PCA [223], NSCT/PCNN [191], WT/PCNN [281], Laplacian/ histogram equalization [267], GA/WT [289], DTW/PCA [290], etc. The objective is to increase the performance of conventional medical image fusion systems, and to meet the needs of real medical applications.…”

Section: Critical Discussion About Multimodal Fusion Techniquesmentioning

confidence: 99%

“…It retains the corresponding spectral characteristic of each pixel and transforms all the luminance information into a high-resolution panoramic image. This technique proposed by many works [229][230][231] is very simple, effective on the computer level and has a faster processing time. It produces RGB images with a high degree of contrast.…”

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confidence: 99%

“…The weighted average value is assigned to each pixel of the input image to obtain the value of the corresponding pixel in the output image. This technique used in some works [217,231,[237][238][239] improves the reliability of detection. However, there is a risk of increasing noise.…”

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confidence: 99%

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A Survey on Computer-Aided Diagnosis of Brain Disorders through MRI Based on Machine Learning and Data Mining Methodologies with an Emphasis on Alzheimer Disease Diagnosis and the Contribution of the Multimodal Fusion

2020

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Computer-aided diagnostic (CAD) systems use machine learning methods that provide a synergistic effect between the neuroradiologist and the computer, enabling an efficient and rapid diagnosis of the patient’s condition. As part of the early diagnosis of Alzheimer’s disease (AD), which is a major public health problem, the CAD system provides a neuropsychological assessment that helps mitigate its effects. The use of data fusion techniques by CAD systems has proven to be useful, they allow for the merging of information relating to the brain and its tissues from MRI, with that of other types of modalities. This multimodal fusion refines the quality of brain images by reducing redundancy and randomness, which contributes to improving the clinical reliability of the diagnosis compared to the use of a single modality. The purpose of this article is first to determine the main steps of the CAD system for brain magnetic resonance imaging (MRI). Then to bring together some research work related to the diagnosis of brain disorders, emphasizing AD. Thus the most used methods in the stages of classification and brain regions segmentation are described, highlighting their advantages and disadvantages. Secondly, on the basis of the raised problem, we propose a solution within the framework of multimodal fusion. In this context, based on quantitative measurement parameters, a performance study of multimodal CAD systems is proposed by comparing their effectiveness with those exploiting a single MRI modality. In this case, advances in information fusion techniques in medical imagery are accentuated, highlighting their advantages and disadvantages. The contribution of multimodal fusion and the interest of hybrid models are finally addressed, as well as the main scientific assertions made, in the field of brain disease diagnosis.

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Section: Critical Discussion About Multimodal Fusion Techniquesmentioning

confidence: 99%

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confidence: 99%

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A Survey on Computer-Aided Diagnosis of Brain Disorders through MRI Based on Machine Learning and Data Mining Methodologies with an Emphasis on Alzheimer Disease Diagnosis and the Contribution of the Multimodal Fusion

2020

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“…PSNR could also be optimized to sharpen images using eight filter directions defined by the two parameter values [17]. The Weighted Average Brovey Transform method is used to merge two images to create a new image, which increases PSNR while decreasing MSE [18]. The MSE and PSNR parameters are also considered when analyzing the performance of the JPEG Algorithm [19].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Quality of Natural Dyes in Weaving Exposed to Sunlight Using MSE and PSNR Parameters

Batarius

Sinlae

Fahik

2022

J. RESTI (Rekayasa Sist. Teknol. Inf.)

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It is widely assumed that natural dyes in weaving degrade in quality when exposed to sunlight for an extended period of time. This indication is clearly visible to the naked eye. There is currently no standard for evaluating the quality of natural dyes. The Boti tribe's weaving on Timor Island, East Nusa Tenggara Province, is one type of weaving that uses natural dyes. The dye is made from corn flour and a combination of "nobah" leaves and the bark of the "bauk ulu" tree (from the local language). White (from corn flour) and blue-black are the colors produced by dyeing the yarn. The purpose of this research is to examine the image quality of the Boti tribe's woven fabric. The parameters used were Means Square Error (MSE), Peak Signal to Noise (PSNR), and RGB values. The image of the weaving used as a reference is compared to the image of the sun-dried weaving. The image capture distance was 30 cm, and the cropped RGB image size was 423x623x3. The experimental method was used in the research. The drying time was one hour, and it was repeated every one hour between 10:00 and 15:00 local time. The sun-dried images were photographed, and parameter comparisons were performed for analysis. The results demonstrated that the MSE and PSNR methods were effective in measuring the image quality of weaving dyed with natural dyes. The average value has changed by 8.42% for the R value, 8.58% for the G value, and 9.68% for the B value. The average PSNR for RGB images is 9.44288 dB, and the MSE is 7477.52. For grayscale images, the average PSNR is 10.52 dB and the average MSE is 5832.06.

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