Abstract: Methods and apparatus are disclosed for digital image restoration. The method including the steps of receiving an external deteriorated image, and generating N restoration images by using a preset PSF and an image restoration filter without computing a PSF of the input deteriorated image, dividing the restoration images into window parts of a predetermined window size, computing absolute values of differences among peripheral pixels within the divided window parts, selecting only a high frequency part, and analyzing focus deterioration; determining weights of the N restoration images, selecting window parts having high weights, and integrating the selected window parts into one image and comparing a degree of restoration of the integrated image with a preset degree of restoration, and outputting the integrated image as a resultant image when the degree of restoration of the integrated image is higher than the preset degree of restoration.

Abstract: Methods and apparatus are disclosed for digital image restoration. The method including the steps of receiving an external deteriorated image, and generating N restoration images by using a preset PSF and an image restoration filter without computing a PSF of the input deteriorated image, dividing the restoration images into window parts of a predetermined window size, computing absolute values of differences among peripheral pixels within the divided window parts, selecting only a high frequency part, and analyzing focus deterioration; determining weights of the N restoration images, selecting window parts having high weights, and integrating the selected window parts into one image and comparing a degree of restoration of the integrated image with a preset degree of restoration, and outputting the integrated image as a resultant image when the degree of restoration of the integrated image is higher than the preset degree of restoration.

Abstract: Disclosed are a method for removing noise in an image, including the steps of: dividing image data contained in the image into predetermined unit areas; calculating each threshold corresponding to the unit area by using values of pixels contained in the unit area; detecting whether a first pixel containing impulsive noise exists in the unit area by using the calculated threshold; applying a median filter to the first pixel in the case the first pixel is detected; identifying a second pixel adjacent to the first pixel in the case the median filter is applied to the first pixel; and applying a mean-variance filter to the second pixel, and a system thereof.