An Efficient Pan-Sharpening Method via a Combined Adaptive PCA Approach and Contourlets

Shah, Vijay; Younan, Nicolas H.; King, Roger L.

doi:10.1109/tgrs.2008.916211

Cited by 555 publications

(248 citation statements)

References 24 publications

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“…PCA distort the spectral characteristics of the mu ltispectral data and decreased quality of the image [3]. The adaptive PCA approach provides efficient spectral transformation between the two images by selecting the best principal co mponent to be replaced by the panchromatic image with high spatial resolution [6].…”

Section: National Conference On Emerging Trends In Computer Electricmentioning

confidence: 99%

Theoretical Study of Image Fusion Techniques: A Review

2015

IJAERD

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Abstract-the goal of image fusion is to combine relevant information from two or more images of the same view in to single image. The result of image fusion is a new fused image which is more suitable for human being and machine discernment for further image-processing tasks like segmentation, feature taking out and objects recognition. In this paper the image fusion techniques described using the PCA, and wavelet family. Principal component analysis (PCA) is a wellknown scheme for feature extraction and dimension reduction. In DCT low frequency region of the image has large DCT coefficient. S o it has very good energy compactness properties. In DWT image are di viding in low sub ban ds and high sub bands are fused using various fusion methods. Finally, the output of the fused image is obtained by applying inverse wavelet transform on the fused coefficients of low sub bands and high sub bands. Where in curvelet it given smooth cured edge detection. Above technique mainly done in two domain: spatial domain and transform domain where it performed fusion at three different processing levels which are pixel level, feature level and decision level according to the stage at which the fusion takes place. This is depends on the required application.

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Section: National Conference On Emerging Trends In Computer Electricmentioning

confidence: 99%

Theoretical Study of Image Fusion Techniques: A Review

2015

IJAERD

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“…The typical fusion algorithms based on MRA include the à trous wavelet image fusion algorithm which adopts translation invariant and undecimated wavelet transform technique [50,58], and the fusion algorithm based on the generalized Laplacian pyramid (GLP) [54]. Some fusion algorithms use wavelet decomposition and CS jointly, such as the fusion algorithm combining wavelet decomposition with PCA [9,59,60] or IHS transform [9,61,62]. A Hybrid pan-sharpening algorithm combining Laplacian filtering and CS-based fusion can be found in [63].…”

Section: A Short Overview Of Existing Pan-sharpening Algorithmsmentioning

confidence: 99%

A Parallel Computing Paradigm for Pan-Sharpening Algorithms of Remotely Sensed Images on a Multi-Core Computer

2014

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Pan-sharpening algorithms are data-and computation-intensive, and the processing performance can be poor if common serial processing techniques are adopted. This paper presents a parallel computing paradigm for pan-sharpening algorithms based on a generalized fusion model and parallel computing techniques. The developed modules, including eight typical pan-sharpening algorithms, show that the framework can be applied to implement most algorithms. The experiments demonstrate that if parallel strategies are adopted, in the best cases the fastest times required to finish the entire fusion operation (including disk input/output (I/O) and computation) are close to the time required to directly read and write the images without any computation. The parallel processing implemented on a workstation with two CPUs is able to perform these operations up to 13.9 times faster than serial execution. An algorithm in the framework is 32.6 times faster than the corresponding version in the ERDAS IMAGINE software. Additionally, no obvious differences in the fusion effects are observed between the fusion results of different implemented versions.

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“…In recent years wavelet transforms have been successfully used. In [12] authors use wavelet packet transform to fuse Quickbird panchromatic and multispectral data fusion. But there are certain drawbacks of wavelet transform worth to be mentioned.…”

Section: Introductionmentioning

confidence: 99%

Image Fusion Scheme based on Wavelet Transformation

Ahmed¹,

Sultana²,

Sattar³

2018

IJCA

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The paper focuses on image fusion between multi-spectral images and panchromatic images using a gradient based wavelet analysis method with image processing traits. For highlighting the core features of source images, preprocessing is accomplished. A new gradient technique is developed based on wavelet transformation. As of gradient process, for a multi-spectral image, every pixel having 4 neighbors of each of them. The summation that we do matches those of the multi-spectral images that we have selected. Two major considerations for gradient are considered. One is for the pixel values in the multi-spectral images region and other is the gradient pixel values that are at the boundary. Once we have calculated these values, we transfer these values from the multi-spectral images onto the panchromatic image and then rest of the values outside the mask are kept as same. Since we are working on the RGB images, we copied the RGB channels directly. By calculating bigger gradient of the two images either in multi-spectral images or panchromatic images and then construct the final image using inverse wavelet transformation. The proposed method is experimented on satellite, medical and natural images. In all the cases, this method shown superiority with existing methods. General TermsGradient pyramid, spatial frequency, Haar fusion, panchromatic image.

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An Efficient Pan-Sharpening Method via a Combined Adaptive PCA Approach and Contourlets

Cited by 555 publications

References 24 publications

Theoretical Study of Image Fusion Techniques: A Review

Theoretical Study of Image Fusion Techniques: A Review

A Parallel Computing Paradigm for Pan-Sharpening Algorithms of Remotely Sensed Images on a Multi-Core Computer

Image Fusion Scheme based on Wavelet Transformation

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