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This paper proposes a method to estimate the local sharpness of an optical system through the wavelet-based analysis of a large set ofimages it acquired. Assuming a space-invariant distribution of image features, such as in the aerial photography context, the proposedapproach produces a sharpness map of the imaging device over 16 × 16 pixels blocks that enables, for instance, the detection of opticaldefects and the qualification of the mosaicking of multiple sensor images into a larger composite image. The proposed analysis isbased on accumulating of the edge maps corresponding to the first levels of the Haar Transform of each image of the dataset, followingthe intuition that statistically, each pixel will see the same image structures. We propose a calibration method to transform theseaccumulated edge maps into a sharpness map by approximating the local PSF (Point Spread Function) with a Gaussian blur

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

MULTISCALE HAAR TRANSFORM FOR BLUR ESTIMATION FROM A SET OF IMAGES