Remote Sensing Applications and Decision Support

Multiresolution image fusion using edge-preserving filters

[+] Author Affiliations
Kishor P. Upla, Sharad Joshi

Sardar Vallabhbhai National Institute of Technology, Department of Electronics and Communication, Surat-395 007, Gujarat, India

Manjunath V. Joshi

Dhirubhai Ambani Institute of Information and Communication Technology, ICT, Gandhinagar-382 007, Gujarat, India

Prakash P. Gajjar

Government Polytechnic for Girls, Department of Electronics and Communication, Surat-395 007, Gujarat, India

J. Appl. Remote Sens. 9(1), 096025 (Jul 24, 2015). doi:10.1117/1.JRS.9.096025
History: Received October 16, 2014; Accepted June 25, 2015
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Abstract.  We propose two approaches of multiresolution image fusion using multistage guided filter and difference of Gaussians (DoGs). In a multiresolution image fusion problem, the given multispectral (MS) and panchromatic (Pan) images have high spectral and high spatial resolutions, respectively. One can obtain the fused image using these two images by injecting the missing high frequency details from the Pan image into the MS image. The quality of the final fused image will then depend on the method used for high frequency details extraction and also on the technique for injecting these details into the MS image. Specifically, we have chosen the guided filter and DoGs for detail extraction since these are more versatile in applications involving feature extraction, denoising, and so on. The detail extraction process in the fusion approach using a guided filter exploits the relationship between the Pan and MS images by utilizing one of them as a guidance image while extracting details from the other. The final fused image is obtained by adding the extracted high frequency details to the corresponding MS image. This way, the spatial distortion of the MS image is reduced by consistently combining the details obtained using both MS and Pan images. In the fusion method using DoGs, the high frequency details are extracted in the first and second levels by subtracting the blurred images of the original Pan. The extracted details at both DoGs are added to the MS image to obtain the final fused image. Advantages and disadvantages of each method are discussed and the comparison of the results is shown between the two. The results are also compared with the traditional and the state-of-the-art methods using the images captured using different satellites such as Quickbird, Ikonos-2, and Worldview-2. The quantitative assessment is evaluated using the conventional measures as well as using a relatively new index, i.e., quality with no reference which does not require a reference image. The results and measures clearly show that there is promising improvement in the quality of the fused image using the proposed approaches.

© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Kishor P. Upla ; Sharad Joshi ; Manjunath V. Joshi and Prakash P. Gajjar
"Multiresolution image fusion using edge-preserving filters", J. Appl. Remote Sens. 9(1), 096025 (Jul 24, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.096025


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