This method incorporates a range of shapes and neighborhoods at multiple scales. Then the de-noised image is subjected to the multi-resolution Top-hat to optimize the contrast.
These metrics are sensitive to structure, texture, edges and local homogeneity of image objects. The proposed approach employs first a wavelet transform trained using a suite of ‘degree of over-smoothing’ metrics (DOSM) for image de-noising. This paper focuses on developing a de-noising and contrast enhancement pipeline for KH-9 HEXAGON MCS and PCS over urban regions.
Although great efforts have been made by the scientific community to develop applications that utilize KH-9 HEXAGON images, little attention has been paid to de-noising and contrast enhancement of these images particularly over urban landscapes. In 20–2022, KH-9 HEXAGON mapping camera system (MCS) and panoramic camera system (PCS) images were made available to the public, respectively.
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