Radiometric Principle-Based Radiometric Normalization Method for SAR Images Mosaic

Liu, Rui; Wang, Feng; Jiao, Niangang; Yu, Wei; You, Hongjian; Liu, Fangjian

doi:10.1109/lgrs.2022.3184746

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…In accordance with Equation (1), a radiometric principle-based radiometric normalization method [29] is employed to eliminate the radiometric differences between images by analyzing the radiometric principle of SAR.…”

Section: Geometric and Radiometric Preprocessing Of Sar Imagementioning

confidence: 99%

Multi-View Data-Based Layover Information Compensation Method for SAR Image Mosaic

Liu,

Wang,

Jiao

et al. 2024

Remote Sensing

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Currently, massive Synthetic Aperture Radar (SAR) images acquired from numerous SAR satellites have been widely utilized in various fields, and image mosaicking technology provides important support and assistance for these applications. The traditional mosaic method selects specific SAR images that can cover the region of interest (ROI) from redundant data to produce “One Map”. However, an SAR image suffers from severe geometric distortion, especially in mountainous areas, which inevitably reduces the utilization of mosaic image. Therefore, a multi-view data-based layover information compensation (MDLIC) method for SAR image mosaic is proposed, aiming to take full advantage of multi-view data to compensate for the missing information in the layover area of the SAR image. This is performed to improve the information content of the mosaic image and realize efficient thematic information extraction and analysis. First, the calculation of the object-space extent of all images and the division of object-space grid are completed on the basis of geometric and radiometric preprocessing. Then, according to the transformation relationship between the object-space and the image-space, the sampling rate image of each image corresponding to the object-space grid is generated, which determines the layover area and the layover degree in each image. Finally, the information compensation strategy is implemented in accordance with the sampling rate image to realize the compensation of the layover information. The feasibility and effectiveness of the MDLIC method are verified by using multiple SAR images from the Chinese Gaofen-3 01 satellite as datasets for experiments. The experimental results indicate that the MDLIC method can obtain mosaic images with richer information compared with the traditional method, while still providing satisfactory results.

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Section: Geometric and Radiometric Preprocessing Of Sar Imagementioning

confidence: 99%

Multi-View Data-Based Layover Information Compensation Method for SAR Image Mosaic

Liu,

Wang,

Jiao

et al. 2024

Remote Sensing

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“…Areas filled with no-data value often presented as blank due to the truncation of multi-projections, which influence the visual effect of the SAR TDOM. Therefore, different SAR TDOMs are fused together by the radiometric-principle-based radiometric normalization (RPRN) method [23].…”

Section: B Sar Tdom Productionmentioning

confidence: 99%

SAR True Digital Ortho Map Production for Target Geometric Structure Preservation

Jiao,

Wang,

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Geometric structural information of objects in SAR images is of great significance in target detection and analysis. Existed orthorectification methods of SAR images generally follow the traditional routes of optical images, resulting in suffering from the influence of layover and bring difficulties in image analysis or target extraction without sufficient prior knowledge. Therefore, this paper proposes a highest projection principle based SAR true digital ortho maps (TDOM) production method for the restoration of geometric structural information of targets. First, ground control information extracted from the high precision digital surface model (DSM) is applied to calibrate the geolocation error of original SAR images. Then, the highest projection principle and the visibility detection is utilized to reduce the influence of layover. To preserve the structural information of targets, multi-view SAR TDOMs are integrated and compensated to generate a fused SAR TDOM image similar as opticla-view. Two Gaofen-3 (GF-3) SAR Spotlight images are included to verify the performance of our proposed method. Experimental results are compared qualitatively in visual effects and quantitatively in geolocation accuracy. The results indicate that the produced SAR TDOMs can preserve the structural information of targets and provide more similar geometric structural information as optical images, which will effectively improve the efficiency in interpretation of ortho-rectified SAR images. Index Terms-Synthetic aperture radar, true digital ortho map (TDOM), layover area, geometric structural information.

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“…They were also able to achieve intensity correction for a range of highresolution images using a regionally independent linear model, in accordance with a low-resolution reference image that was created. Furthermore, by employing a global quantization technique along with a radiometric adjustment model, Liu et al [33] successfully removed the radiative disparities in SAR image stitching.…”

Section: Introductionmentioning

confidence: 99%

Color Correction and Naturalness Restoration for Multiple Images With Uneven Luminance

Xu,

Hong,

Tong

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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When multiple synthetic aperture radar (SAR) images are stitched together, the intensity disconnects between them can have a significant impact on the mosaic's quality. Many approaches focus on decreasing the intensity differences between images while ignoring the issue of image quality improvement. This study provides an algorithm for color correction and naturalness restoration for multiple images with uneven luminance in order to generate high-quality mosaics.To increase the illuminance component's naturalness, the image is first divided into illuminance and reflectance components, and the illuminance component is subjected to adaptive luminance improvement and contrast enhancement. Using a color consistency optimization approach, the intensity disparities between illuminance components are subsequently minimized. The reflectance and enhanced illuminance components are then combined to produce an improved image. After that, the enhanced image is mosaicked using multi-band blending. Finally, the intensity differences between the enhanced images are further decreased using the block-based Wallis transform based on the mosaic.We assessed the proposed method on 402 Sentinel-1 images covering the majority of China's land area to verify its robustness. When compared to similar algorithms, our strategy reduces the color distance (CD) by about 36.72%, improves the average gradient (AG) by around 89.44%, and increases the patch-based contrast quality index (PCQI) by roughly 32.85%. The experimental outcomes reveal that our approach has considerable advantages in terms of color correction and image quality improvement, both visually and quantitatively.

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Radiometric Principle-Based Radiometric Normalization Method for SAR Images Mosaic

Cited by 5 publications

References 15 publications

Multi-View Data-Based Layover Information Compensation Method for SAR Image Mosaic

Multi-View Data-Based Layover Information Compensation Method for SAR Image Mosaic

SAR True Digital Ortho Map Production for Target Geometric Structure Preservation

Color Correction and Naturalness Restoration for Multiple Images With Uneven Luminance

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