Title: Design of filter for image de-noising using discrete wavelet transform for ASIP

Authors: Mood Venkanna; Rameshwar Rao; P. Chandra Sekhar

Addresses: Department of Electronics and Communication Engineering, University College of Engineering, Osmania University, India ' Department of Electronics and Communication Engineering, University College of Engineering, Osmania University, India ' Department of Electronics and Communication Engineering, University College of Engineering, Osmania University, India

Abstract: Application specific instruction-set processors (ASIP) is a customised processor for user specific application. Though a significant research has been done on this, still it is most promising technology, due to lack of efficient methodologies for designing the processor configuration according to the applications. Again ASIP solution explores the trade-off between the dedicated hardware design and flexibility among software. It endeavours to fulfil the functionality of an algorithmic with low power costs and less complexity. In this paper, an approach is considered to design a processor for image de-noising. The design of suitable filter is an important task for the transmission and real-time processing. Designing ASIPs requires a suitable design of custom data path simultaneously modify the instruction-set, decoder including the compiler. We present an ASIP based on custom architecture design using the discrete wavelet transform (DWT) as a filter. It starts with the general purpose data path like MIPS. It customises the data path iteratively for better power utilisation, usable area and performance. All the experiments have been synthesised using Xilinx FPGA and also verified in Spartan board. The subjective evaluations of the filter is analysed through various figures. Further it is implemented in HDL to support the customised processor.

Keywords: image filtering; wavelet transform; application specific instruction-set processor; ASIP; impulse noise; field programming gate array; FPGA; VHDL.

DOI: 10.1504/IJCVR.2021.113400

International Journal of Computational Vision and Robotics, 2021 Vol.11 No.2, pp.201 - 213

Accepted: 18 Sep 2019
Published online: 03 Mar 2021 *

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