earticle

영어

This paper presents the evaluation of two approaches, widely used in the inpainting literature, applied in the context of the atmospheric noise removal, such as fog, clouds - dense and sparse - and shadows, which often occur in remote sensing images. The presence of such elements aect, in many ways, the image processing in an environmental or urban monitoring, and also in the steps of the digital image processing, suchlike segmentation and classication. Whilst one approach uses a technique of interpolation for the dissemination of information by a multidimensional Discrete Cosine Transform (DCT) smoothing method, the other one is based on second-order partial dier- ential equations methods (PDE). This PDE-based development uses the heat diusion and thin-plate spline methods to achieve their solutions with the aid of the nite-dierence method. To proceed the methods evaluation, this work uses the kappa coecient and the Peak Signal-to-Noise Ratio index (PSNR). The metrics indicate the eectiveness of the DCT strategy, which produces higher quality images, specially when comparing the results obtained by the use of dierential equations modeled by thin-plate spline. The visual aspect of images is clearly an important factor for measuring the eectiveness of any image processing, so, in addition to numerical metrics, are presented the nine images used to evaluate both methods.