Combined interpolation—restoration of Landsat images through FIR filter design techniques

L. M. G. FONSECA, G. S. S. D. PRASAD, N. D. A. MASCARENHAS
1993 International Journal of Remote Sensing  
In digital image processing for remote sensing there is often a need to interpolate an image. Examples occur in scale magnification, image registration, geometric correction, etc. On the other hand, this image can be subject to several sources of degradation and it would be interesting to compensate also for this degradation in the interpolation process. Therefore, this article addresses the problem of combining interpolation and restoration in a single operation, thereby reducing the
more » ... nal effort. This is done by means of two-dimensional, separable, Finite Impulse Response (FIR) filters. The ideal low pass FIR filter for interpolation is modified to account for the restoration process. The Modified Inverse Filter (MIF) and the Wiener Filter (WF) are used for this purpose. The proposed methods are applied to the interpolation-restoration of Landsat-5 Thematic Mapper data. The later process takes into account the degradation due to optics, detector and electronic filtering. A comparison with the Parametric Cubic Convolution (PCC) technique is made. The experimental results consist of interpolation-restoration processes of Landsat-5 Thematic Mapper images from 30 m to 15 m (scale magnification) but they could also be generalized to include deblurring on more general interpolation problems, like geometric correction
doi:10.1080/01431169308904292 fatcat:x5j3ru6jljce3owhvw2l3lms7a