Image Fusion of Noisy Images Based on Simultaneous Empirical Wavelet Transform

Abstract

Fusion image is the method of extracting the relevant information from two or more identical input images into one scene and creating a new image. This method allows the new image to provide comprehensive information about the wand, leading to a visual understanding of the human being. Fusion image application in image processing is an important issue. Applications in many fields such as photography, microscopy, astronomy, medical imaging, satellite imagery, machine vision, biology are monitored. In this study first, an image fusion method, suggested recently based on transform empirical wavelet, was implemented in which coefficients were obtained by processing the input images. Then they were combined by applying the rules. The aim of this study is to investigate the noise effect and to remove the noise in the aforementioned suggested method. First, the noise was added to the images, and the images were decomposed into layers or coefficients. Second, by thresholding the coefficients, the noise was removed. Then the coefficients were combined based on the rules to obtain the final coefficients. In the end, the final coefficients were used to obtain the fused image. The results show that the noise removal of images during image fusion is much better and more effective than denoising before image fusion, and the demonstration of the method is proved by obtaining better results in comparison to some existing methods.

A New Security Alarm Based on Interaction

“…In the vicinity of the house, inform the home owner of the possibility of tampering and the image of the passerby through a smart phone application, or if the owner of the house is not available and the possibility of tampering is certain, call the police and report the situation. [10,11]. The underdeveloped methods of producing security alarm systems were replaced by programmed security alarm systems in the late 18th century.…”

Two-Scale Multimodal Medical Image Fusion Based on Structure Preservation

“…Finally, the final fused result can be obtained through inverse transformation. At present, scholars around the world have proposed many image fusion methods in the transform domain ( Mao et al, 2020 ), such as the wavelet-based image fusion methods proposed in Sumir and Gahan (2018) , Panigrahy et al (2020b) , and Rahmani et al (2020) , the image fusion algorithms using non-subsampled contourlet transform (NSCT) proposed in Das and Kundu (2012) , Zhu et al (2019) , Liu J. et al (2020) , and Panigrahy et al (2020a) , and the image fusion algorithms using non-subsampled shearlet transform (NSST) ( Liu et al, 2017a ; Ganasala and Prasad, 2020 ; Panigrahy et al, 2020c ). These algorithms have achieved good fusion effects.…”

Reversible Information of Encrypted Image Based on Feature Difference Detection and Wavelet Transform

“…For example, the pixel value of 257 will suddenly change to 1, and a white pixel will suddenly change into a black one, which will cause salt pepper noise when the image is displayed and seriously affect the image quality. To prevent overflow, most solutions use location maps to indicate which coefficients cannot be changed, in order to pass the map to the decoding end [ 16 ].…”