Shadow Detection and Removal for Occluded Object Information Recovery in Urban High-Resolution Panchromatic Satellite Images

Su, Nan; Zhang, Ye; Tian, Shu; Yan, Yiming; Miao, Xinyuan

doi:10.1109/jstars.2016.2570234

Cited by 53 publications

(21 citation statements)

References 30 publications

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“…The projection-contours of the building were extracted from each SGSPs using the image matting methods [ 13 ] and some manual correction. Since the building has a complex 3D shape, we initialized it into 27 units ( ξ model = { ξ b_i }, i = 1, 2, …, 27) as Figure 9 e, including 25 outer-units and 2 inner-units.…”

Section: Methodsmentioning

confidence: 99%

A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs

Yan

Zhao

et al. 2017

Sensors

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In this paper, a novel framework of the 3D reconstruction of buildings is proposed, focusing on remote sensing super-generalized stereo-pairs (SGSPs). As we all know, 3D reconstruction cannot be well performed using nonstandard stereo pairs, since reliable stereo matching could not be achieved when the image-pairs are collected at a great difference of views, and we always failed to obtain dense 3D points for regions of buildings, and cannot do further 3D shape reconstruction. We defined SGSPs as two or more optical images collected in less constrained views but covering the same buildings. It is even more difficult to reconstruct the 3D shape of a building by SGSPs using traditional frameworks. As a result, a dynamic multi-projection-contour approximating (DMPCA) framework was introduced for SGSP-based 3D reconstruction. The key idea is that we do an optimization to find a group of parameters of a simulated 3D model and use a binary feature-image that minimizes the total differences between projection-contours of the building in the SGSPs and that in the simulated 3D model. Then, the simulated 3D model, defined by the group of parameters, could approximate the actual 3D shape of the building. Certain parameterized 3D basic-unit-models of typical buildings were designed, and a simulated projection system was established to obtain a simulated projection-contour in different views. Moreover, the artificial bee colony algorithm was employed to solve the optimization. With SGSPs collected by the satellite and our unmanned aerial vehicle, the DMPCA framework was verified by a group of experiments, which demonstrated the reliability and advantages of this work.

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Section: Methodsmentioning

confidence: 99%

A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs

Yan

Zhao

et al. 2017

Sensors

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“…Method [19] for both natural & satellite images is appropriate Shadows may occlude objects in highly resolution panchromatic satellite images, particularly in urban scenes, to reduce or lose their detail. Shadow removal is an important processing method for the analysis & application of the images [20] to recover the occluded details of objects. Authors in [21] suggested an approach to shadow removal focused on a subregion that suits the transition of illumination.…”

Section: Literature Surveymentioning

confidence: 99%

Shadow Detection and Removal Techniques in Aerial Images

Kanojia*,

Chourasia

2020

IJITEE

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One of the complicated tasks is to detect & remove Shadow from single images of aerial images. Significant research is being carried out on various techniques of shadow detection. Over past decades, many shadow identification & removal approaches have been applied. Shadows are optical effects that arise when a region in the scene occurs when the primary light. Shadows are all over around us, so there is no confusion by their appearance. In this paper we provide an overview of the different methods used in the aerial images to identify & eliminate shadows & also provide their comparative study.

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“…However, this was difficult, since there were no ground truth data. In this paper, we referred to the quantitative analysis method of shadow removal [34,35], which selected the samples to compare the gray values between the restored pixels in the shaded regions and adjacent pixels in the nonshaded regions for the same land cover, since they should share similar values.…”

Section: Quantitative Analysismentioning

confidence: 99%

Virtual Restoration of Stained Chinese Paintings Using Patch-Based Color Constrained Poisson Editing with Selected Hyperspectral Feature Bands

Zhou

Hou

et al. 2019

Remote Sensing

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Stains, as one of most common degradations of paper cultural relics, not only affect paintings’ appearance, but sometimes even cover the text, patterns, and colors contained in the relics. Virtual restorations based on common red–green–blue images (RGB) which remove the degradations and then fill the lacuna regions with the image’s known parts with the inpainting technology could produce a visually plausible result. However, due to the lack of information inside the degradations, they always yield inconsistent structures when stains cover several color materials. To effectively remove the stains and restore the covered original contents of Chinese paintings, a novel method based on Poisson editing is proposed by exploiting the information inside the degradations of selected three feature bands as the auxiliary information to guide the restoration since the selected feature bands captured fewer stains and could expose the covered information. To make the Poisson editing suitable for stain removal, the feature bands were also exploited to search for the optimal patch for the pixels in the stain region, and the searched patch was used to construct the color constraint on the original Poisson editing to ensure the restoration of the original color of paintings. Specifically, this method mainly consists of two steps: feature band selection from hyperspectral data by establishing rules and reconstruction of stain contaminated regions of RGB image with color constrained Poisson editing. Four Chinese paintings (‘Fishing’, ‘Crane and Banana’, ‘the Hui Nationality Painting’, and ‘Lotus Pond and Wild Goose’) with different color materials were used to test the performance of the proposed method. Visual results show that this method can effectively remove or dilute the stains while restoring a painting’s original colors. By comparing values of restored pixels with nonstained pixels (reference of their same color materials), images processed by the proposed method had the lowest average root mean square error (RMSE), normalized absolute error (NAE), and average differences (AD), which indicates that it is an effective method to restore the stains of Chinese paintings.

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Shadow Detection and Removal for Occluded Object Information Recovery in Urban High-Resolution Panchromatic Satellite Images

Cited by 53 publications

References 30 publications

A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs

A Dynamic Multi-Projection-Contour Approximating Framework for the 3D Reconstruction of Buildings by Super-Generalized Optical Stereo-Pairs

Shadow Detection and Removal Techniques in Aerial Images

Virtual Restoration of Stained Chinese Paintings Using Patch-Based Color Constrained Poisson Editing with Selected Hyperspectral Feature Bands

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