Removal of Stripes in Remote Sensing Images Based on Statistics Combined with Image Enhancement

A method to remove stripes from remote sensing images is proposed based on statistics and a new image enhancement method.The overall processing steps for improving the quality of remote sensing images are introduced to provide a general baseline.Due to the differences in satellite sensors when producing images,subtle but inherent stripes can appear at the stitching positions between the sensors.These stitchingstripes cannot be eliminated by conventional relative radiometric calibration.The inherent stitching stripes cause difficulties in downstream tasks such as the segmentation,classification and interpretation of remote sensing images.Therefore,a method to remove the stripes based on statistics and a new image enhancement approach are proposed in this paper.First,the inconsistency in grayscales around stripes is eliminated with the statistical method.Second,the pixels within stripes are weighted and averaged based on updated pixel values to enhance the uniformity of the overall image radiation quality.Finally,the details of the images are highlighted by a new image enhancement method,which makes the whole image clearer.Comprehensive experiments are performed,and the results indicate that the proposed method outperforms the baseline approach in terms of visual quality and radiation correction accuracy.

A spatial multi-scale integer coding method and its application to three-dimensional model organization

With the rapid development of digital earth,smart city,and digital twin technology,the demands of three-dimensional model data’s application is getting higher and higher.These data tend to be multi-objectification,multi-type,multi-scale,complex spatial relationship,and large amount,which brings great challenges to the efficient organization of them.This paper mainly studies the organization of three-dimensional model data,and the main contributions are as follows:1)A integer coding method of three dimensional multi-scale grid is proposed,which can reduce the four-dimensional(spatial dimension and scale dimension)space into one-dimensional,and has better space and scale clustering characteristics by comparing with various types of grid coding.2)The binary algebra calculation method is proposed to realize the basic spatial relationship calculation of three-dimensional grid,which has higher spatial relationship computing ability than 3D-Geohash method;3)The multi-scale integer coding method is applied to the data organization of three-dimensional city model,and the experiment results show that:it is more efficient and stable than the threedimensional R-tree index and Geohash coding method in the establishment of index and the query of three dimensional space.