Abstract
Since remote sensing images are one of the main sources for people to obtain required information, the quality of the image becomes particularly important. Nevertheless, noise often inevitably exists in the image, and the targets are usually blurred by the acquisition of the imaging system, resulting in the degradation of quality of the images. In this paper, a novel preprocessing algorithm is proposed to simultaneously smooth noise and to enhance the edges, which can improve the visual quality of remote sensing images. It consists of an improved adaptive spatial filter, which is a weighted filter integrating functions of both noise removal and edge sharpness. Its processing parameters are flexible and adjustable relative to different images. The experimental results confirm that the proposed method outperforms the existing spatial algorithms both visually and quantitatively. It can play an important role in the remote sensing field in order to achieve more information of interested targets.
Highlights
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Key Laboratory of Space-Based Dynamic & Rapid Optical Imaging Technology, Chinese Academy of Sciences, Abstract: Since remote sensing images are one of the main sources for people to obtain required information, the quality of the image becomes important
The test images are acquired by a time-delayed integration (TDI) charge-coupled device (CCD) imaging system, which employs a kind of linear array photoelectric detector
From the calculation results of gray mean gradient (GMG) for the edge region B, we can observe that the Wiener filter (WF), bilateral filter (BF), and average filter (AF) have smaller values than the original image, indicating that they have less information of the targets and only perform edge preservation, while the unsharp masking filter (UMF), BF + UMF and improved adaptive spatial filter (IASF) performs larger edge preservation
Summary
A novel spatial preprocessing algorithm is proposed, called an improved adaptive spatial filter (IASF) It has good capabilities of both edge sharpening and noise smoothing, and its processing parameters are flexible and adjustable relative to different images. It can enhance the edges in the target region without artifacts and smooth the noise in the uniform region without reducing the useful information It renders the IASF filter more appropriate for processing remote sensing images. The experimental results indicate that the proposed method performs better in both visual effect and objective data It can play an important role in the remote sensing field in making images clearer with higher SNR and better display effects
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