Increasing the Speed of Wavelet Image Processing with Decimation Using the Winograd Method

Wavelet processing is actively used for image de noising, compression, and fusion. The high growth rate of quantitative and qualitative characteristics of digital images, lead to the need to increase the speed of wavelet image processing methods and their efficient implementation on modern hardware devices. This paper proposes the Winograd method (WM) to speed up the wavelet image processing methods due to group pixel processing. The scheme of wavelet filtering of images using WM with decimation has been developed. The proposed approach reduced the asymptotic computational complexity of wavelet transform up to 53 % compared to the pixel-by-pixel processing. Estimating the time spent on a hardware device based on a unit-gate model showed that WM reduces device delay up to 67% compared to the direct method. The proposed approach implementation of wavelet image processing on a field-programmable gate arrays and an application-specific integrated circuits is a promising direction for further research.