A fuzzy based hybrid multispectral image fusion method using DWT

Current Science

This study proposes a new multispectral (MS) and panchromatic (PAN) image fusion algorithm based on regionally weighted principal component analysis (RW-PCA) and wavelet. First, the MS images are segmented into spectrally similar regions based on the fuzzy c-means (FCM) clustering method. Secondly, based on the spectral vector's degree of membership in each region, a new RW-PCA method is proposed to fuse the MS and PAN images region by region, and fused MS images are obtained. In the traditional PCA-based fusion method, the MS and PAN images are fused globally with the same transform method. In the proposed RW-PCA-based fusion method, the local spectrum information of the MS images is employed, and the spectral information is better preserved in the fused MS images. Finally, in order to improve the quality of spectral and spatial details, the above fused MS images and the original PAN images are further fused using the wavelet-based fusion method, and the final fused MS images are obtained. Experimental results demonstrated that the proposed image fusion algorithm performs better in spectral preservation and spatial quality improvement than some other methods do.

International Journal of Recent Technology and Engineering (IJRTE), 2019

The high sensor cost for producing images with superior spectral and spatial qualities in remote sensing application have led to the development of image fusion algorithms. Image fusion technique combines a Panchromatic image and a Multispectral image with an aim to produce images with excellent spatial and spectral qualities. One of the major factors that affect the performance of any image fusion algorithm is the capability of the algorithm in extracting the spatial and spectral data from the respective images and how effective the so extracted information is blended together. One of the recently developed spectral domain algorithm to perform image fusion in remote sensing applications is Spatial Frequency Discrete Wavelet Transform abbreviated as SFDWT. The excellence of SFDWT image fusion algorithm is already proven better than the prevailing algorithms based on Discrete Wavelet Transform. This paper is coined with an eye to realize the performance of SFDWT based image fusion al...

—. In this paper, we propose a fuzzy-based multi-spectral (MS) and panchromatic (PAN) image fusion approach which provides a tradeoff solution between spectral and spatial fidelity and is able to preserve more detail in terms of spectral and spatial information. First, we perform principal component analysis on the multi-spectral images and utilise the first principal component to extract matched low and high frequency coefficients. We then apply fuzzy-based image fusion rules to fuse the first principal component with the PAN image, followed by fusing the approximation coefficients. The proposed approach is tested on several satellite images and shown to provide a feasible and effective approach.

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, 2015

Image fusion has found many applications in computer vision, remote sensing, intelligent robots and military purposes. The use of different image fusion algorithms gives precise resultant images.In many remote sensing applications, the quantity of image data from the satellite sensors has been increasing because of advanced sensor technology.To avoid the limitations of single sensor images, multisensory image fusion provides the data that is suitable for further applications by eliminating the problem of lack of information. In this paper, a literature review has been made based on different techniques for combining multispectral images available. It includes IHS transform, High Pass filtering, PCA analysis, ANN, Wavelet transform and DCT. One of the effective techniques to get a good quality image is by using the Fuzzylet Fusion Algorithm in which the advantages of both Stationary Wavelet Transform and Fuzzy logic are combined.

International Journal of Advanced engineering, Management and Science, 2015

In order to find out the fusion algorithm which is best suited for the panchromatic and multispectral images, fusion algorithms, such as PCA and wavelet algorithms have been employed and analyzed. In this paper, performance evaluation criteria are also used for quantitative assessment of the fusion performance. The spectral quality of fused images is evaluated by the ERGAS and Q4. The analysis indicates that the DWT fusion scheme has the best definition as well as spectral fidelity, and has better performance with regard to the high textural information absorption. Therefore, as the study area is concerned, it is most suited for the panchromatic and multispectral image fusion. an image fusion algorithm based on wavelet transform is proposed for Multispectral and panchromatic satellite image by using fusion in spatial and transform domains. In the proposed scheme, the images to be processed are decomposed into sub-images with the same resolution at same levels and different resolutio...

Remote sensing image fusion is the method of gath- ering information from images obtained from sensors of different modalities in order to create an image that is more detailed than the input images. This paper presents a novel method for fusion of low-resolution multispectral (MS) images with a high- resolution panchromatic (PAN) image using Intensity Hue Saturation (IHS) transform and Stationary Wavelet Transform (SWT). Here, the intensity information of the MS image is modified using the intensity information of the PAN image at the wavelet decomposition level providing better resolution to the output image. Finally, CLAHE algorithm is also utilised for improving image’s edge quality. In this paper, we also use parameters like correlation coefficient(CC) and power signal-to- noise ratio(PSNR) to measure the quality of the fused image. From experimental results, we observed that SWT method provides better information ie., image quality. The proposed method is found to show better performance compared to other standard fusion methods like IHS fusion, PCA fusion and DWT fusion.

2020

The fusion technique of the spectral bands captured by the sensors carried onboard satellites is one digital processing method for extracting information and detecting ground targets. Image fusion also known as pan-sharpening-provides the necessary means to combine many images into a single composite image that is suitable in visual interpretation processes or in digital interpretation. The principal objective of this study is to find the best suitable algorithms for obtaining integrative information from several separate images in one combined image. Based on the above, a special software system was designed to implement and test the fusion methods used in remote sensing applications by selecting and applying a Shift Invariant Wavelet Transform (SIWT) method to the remote sensing images and then comparing with four other different image fusion algorithms. Two objective mathematical methods were also used to measure the amount of shared information obtained in the images resulting f...

Int J Remote Sens, 2006

The preservation of spectral characteristics and the retention of high spatial resolution are two key issues in image fusion. Different applications may require different balances between the two. However, the limitation is that only one fused result is possible for most of the commonly used fusion methods; users have no control over how much spatial detail or spectral information should be retained. Both quantitative and qualitative criteria, including mean, standard deviation, entropy, average gradient, spectral distortion, correlation coefficient and visual assessment, were used to evaluate the performance of the proposed fuser. A SPOT (Satellite Pour l'Observation de la Terre) panchromatic image and Landsat Thematic Mapper (TM) images were employed in the evaluation. The results show that the proposed method is slightly better than, or comparable to, commonly used image fusion methods, including Intensity-Hue-Saturation (IHS), principal component analysis (PCA), and two other wavelet-based fusion methods with replacement and with selection strategies, in terms of spectral characteristic preservation and high spatial resolution retention. Moreover, the proposed method can achieve a wide range of balances between spectral characteristic preservation and high spatial resolution retention, and thus is applicable in different applications. low spatial resolution images using the IHS system and then substituting the *Corresponding author.

Lecture notes in networks and systems, 2023

Nowadays the result of infrared and visible image fusion has been utilized in significant applications like military, surveillance, remote sensing and medical imaging applications. Discrete wavelet transform based image fusion using unsharp masking is presented. DWT is used for decomposing input images (infrared, visible). Approximation and detailed coefficients are generated. For improving contrast unsharp masking has been applied on approximation coefficients. Then for merging approximation coefficients produced after unsharp masking average fusion rule is used. The rule that is used for merging detailed coefficients is max fusion rule. Finally, IDWT is used for generating a fused image. The result produced using the proposed fusion method is providing good contrast and also giving better performance results in reference to mean, entropy and standard deviation when compared with existing techniques.

Applied Geomatics, 2014

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