Computationally efficient low-power sigma delta modulation-based image processing algorithm

Autor: Aneela Pathan, Tayab D Memon, Saleem Raza Memon, Rizwan Aziz Mangi
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Mehran University Research Journal of Engineering and Technology, Vol 42, Iss 3, Pp 102-109 (2023)
Druh dokumentu: article
ISSN: 0254-7821
2413-7219
DOI: 10.22581/muet1982.2303.11
Popis: Digital Image Processing has dominated Digital Signal Processing at the cost of more memory, resources, and high computational power. In image processing, filtering transformations and other operations need complex multiplications, and the multiplier is one of the most resources consuming elements. Recently, mitigating the multiplier complexity in the digital signal processing (DSP) algorithms sigma-delta modulation based general purpose and adaptive DSP algorithms are developed in MATLAB and compared with its counterpart multi-bit algorithms for functionality and area-performance-power in FPGA. The contemporary multiplier algorithms are also optimized to overcome the multiplier complexity challenge as computation becomes simple and fast. This paper extends the reported work by investigating the sigma-delta modulation approaches for developing a computationally efficient low-power image processing algorithm. The proposed model is designed, developed, and simulated in MATLAB. The simulation results are analyzed using SNR, MSE, and Peak SNR. The simulation results show that the proposed system can better mitigate the noise effect, making it robust for noisy environment.
Databáze: Directory of Open Access Journals