Low-Latency Wavelet Image Processing Using the Winograd Method with Convolution Step
Abstract
Low-Latency Wavelet Image Processing Using the Winograd Method with Convolution Step
Incoming article date: 05.10.2023Wavelets are widely used in various fields of science and technology for processing 1D signals and multidimensional images. However, technical information processing devices are developing more slowly than the amount of digital data is growing. Computational latency is the most important characteristic of such devices. This paper proposes an implementation of the Winograd method with a convolution step 2 to reduce the latency of wavelet image processing. The proposed scheme for implementing calculations has reduced the asymptotic computational complexity of wavelet processing of 2D images to 53% compared to the direct implemettaion method. A theoretical assessment of the computing device characteristics showed a reduction in latency of up to 67%. A promising direction for further research is the hardware implementation of the proposed approach on modern microelectronic devices.
Keywords: image processing, Winograd method, digital filtering, computational delay, wavelet transform, convolution with step