Abstract
this paper examined the applicability of quantum genetic algorithms to solve optimization problems posed by satellite image enhancement techniques, particularly super-resolution, and fusion. We introduce a framework starting from reconstructing the higher-resolution panchromatic image by using the subpixel-shifts between a set of lower-resolution images (registration), then interpolation, restoration, till using the higher-resolution image in pan-sharpening a multispectral image by weighted IHS+Wavelet fusion technique. For successful super-resolution, accurate image registration should be achieved by optimal estimation of subpixel-shifts. Optimal-parameters blind restoration and interpolation should be performed for the optimal quality higher-resolution image. There is a trade-off between spatial and spectral enhancement in image fusion; it is difficult for the existing methods to do the best in both aspects. The objective here is to achieve all combined requirements with optimal fusion weights, and use the parameters constraints to direct the optimization process. QGA is used to estimate the optimal parameters needed for each mathematic model in this framework “Super-resolution and fusion.” The simulation results show that the QGA-based method can be used successfully to estimate automatically the approaching parameters which need the maximal accuracy, and achieve higher quality and efficient convergence rate more than the corresponding conventional GA-based and the classic computational methods.
Highlights
Image fusion is the process of merging two or more images obtained from two or more sensors for the same scene
The proposed framework of image enhancement based on QGA optimization is fine-tuned by means of three parameters; Transformation matrix of registration, blur kernel for restoration process and injection Intensity Hue Saturation (IHS)+Wavelet fusion weights of the added reconstructed pan high resolution (HR) image to the up-sampled MS bands
Investigating the proposed QGA-based weighted IHS+Wavelet fusion method, by inspecting the quality of enhanced MS fused images; it is noticed that the proposed method preserves the original spectral properties of the added upsampled MS images to a high degree, images are subject to spectral distortions during fusion operations
Summary
Image fusion is the process of merging two or more images obtained from two or more sensors for the same scene. The stand-alone wavelet fusion outperforms other conventional (conv.) fusion techniques, such as IHS, Principal Component Analysis (PCA) in preserving spectral information [8] because it usually injects the high spatial details from the HR image into all three low spatial resolution MS bands. These high spatial information in the HR image have gray values different from that of an MS band. Image restoration and interpolation techniques are implemented to www.ijacsa.thesai.org
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