F-transform; convolution; image processing

Discrete convolution is commonly used operation in the image processing field. The technique modifies an input image in various ways by scalable and easy computation. We are able to achieve many applications such as edge detection, noise reduction or artistic filtering, by selection of the proper kernel. The technique of the F-transform investigated in few last years also modifies an input image in the certain ways. Following paper introduces image processing based on the convolution operation and F-transform approximation with emphasis on similarities and negotiability of the both techniques. As an illustration, we will use the Gaussian convolution kernel and appropriate F-transform basic function for simple noise reduction.

Discrete convolution is commonly used operation in the image processing field. The technique modifies an input image in various ways by scalable and easy computation. We are able to achieve many applications such as edge detection, noise reduction or artistic filtering, by selection of the proper kernel. The technique of the F-transform investigated in few last years also modifies an input image in the certain ways. Following paper introduces image processing based on the convolution operation and F-transform approximation with emphasis on similarities and negotiability of the both techniques. As an illustration, we will use the Gaussian convolution kernel and appropriate F-transform basic function for simple noise reduction.