A Survey on Image Fusion Techniques for Image Enhancement in Digital Image Processing

Kaur, Ravneet; Kaur, Rupinder

doi:10.5120/ijca2018917133

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…Image enhancement is a dependent on digital image processing. Its purpose is to enhance, weaken or remove some information in the image according to specific requirements, so that the original image can be more suitable for observation and analysis [21,22]. In order to recognise the target clearly from the defects target and enhance the contrast between the target area and the background, many experts and scholars have done a lot of research.…”

Section: Introductionmentioning

confidence: 99%

Multi-scale decomposition enhancement algorithm for surface defect images of Si₃N₄ ceramic bearing balls based on stationary wavelet transform

Zhu

Min

et al. 2020

Advances in Applied Ceramics

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In order to improve the detection efficiency and image quality of Si 3 N 4 ceramic bearing balls surface defects, digital image processing technology is used to analyse the information characteristics of Si 3 N 4 ceramic bearing balls surface. A multi-scale decomposition enhancement algorithm for surface defect images of Si 3 N 4 ceramic bearing balls based on the stationary wavelet transform is proposed. By building the surface defects detection system of Si 3 N 4 ceramic bearing balls, the image enhancement program based on stationary wavelet transform with index low-pass filtering and nonlinear transform enhancement is designed. Finally, the effectiveness of the algorithm is verified by experiments. The experimental results show that the algorithm is applied to the surface defects image of Si 3 N 4 ceramic bearing balls can effectively weaken the background noise and surface grinding texture, and enhance the contrast between defects and background clearly. In addition, the binary image is obtained by an adaptive threshold binary algorithm. After removing the tiny points by morphological opening operation, the defects are accurately and completely segmented, and then the Canny operator is used for edge detection to extract the edge contour of defects. When the decomposition level is set to 3, the average calculation time is 0.88 s, which are relatively short and have sufficient precision, and the algorithm can be extended to other kinds of ceramic ball surface damage detection.

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Section: Introductionmentioning

confidence: 99%

Multi-scale decomposition enhancement algorithm for surface defect images of Si₃N₄ ceramic bearing balls based on stationary wavelet transform

Zhu

Min

et al. 2020

Advances in Applied Ceramics

View full text Add to dashboard Cite

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Digital Image Progressive Fusion Method Based on Discrete Cosine Transform

Chen

2023

Journal of Mathematics

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The current progressive fusion methods for digital images have poor denoising performance, which leads to a decrease in image quality after progressive fusion. Therefore, a new method for digital image progressive fusion was proposed based on discrete cosine transform, and its effectiveness was verified through experiments. The experimental results show that the proposed method has a PSNR value higher than 42.13 db in image fusion, both of which are higher than the comparison method, and the fusion effect comparison also has higher image quality. In terms of fusion time, the time of the research method is lower than that of the comparison method when the data volume is between 10 and 100, while in the comparison of structural similarity, the structural similarity of the image fused by the research method is always higher than 0.83. Overall, the fusion method proposed in the study results in higher image quality and is effective in progressive digital image fusion, which is of great significance for practical digital image fusion.

show abstract

A Survey on Image Fusion Techniques for Image Enhancement in Digital Image Processing

Cited by 2 publications

References 7 publications

Multi-scale decomposition enhancement algorithm for surface defect images of Si₃N₄ ceramic bearing balls based on stationary wavelet transform

Multi-scale decomposition enhancement algorithm for surface defect images of Si₃N₄ ceramic bearing balls based on stationary wavelet transform

Digital Image Progressive Fusion Method Based on Discrete Cosine Transform

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A Survey on Image Fusion Techniques for Image Enhancement in Digital Image Processing

Cited by 2 publications

References 7 publications

Multi-scale decomposition enhancement algorithm for surface defect images of Si3N4 ceramic bearing balls based on stationary wavelet transform

Multi-scale decomposition enhancement algorithm for surface defect images of Si3N4 ceramic bearing balls based on stationary wavelet transform

Digital Image Progressive Fusion Method Based on Discrete Cosine Transform

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Product

Resources

About

Multi-scale decomposition enhancement algorithm for surface defect images of Si₃N₄ ceramic bearing balls based on stationary wavelet transform

Multi-scale decomposition enhancement algorithm for surface defect images of Si₃N₄ ceramic bearing balls based on stationary wavelet transform