Computationally efficient wavelet-based low memory image coder for WMSNs/IoT

• Published in: Multidimensional systems and signal processing Vol. 34; no. 3; pp. 657 - 680
• Main Authors: Tausif, Mohd, Khan, Ekram, Pinheiro, Antonio
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2023; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Body area networks; Circuits and Systems; Complexity; Electrical Engineering; Engineering; Image coding; Internet of Things; Multimedia; Signal to noise ratio; Signal,Image and Speech Processing; Wireless sensor networks; Internet of things; Image coding algorithms; Low-memory; Discrete wavelet transform; Low complexity; Visual sensors
• ISSN: 0923-6082; 1573-0824
• DOI: 10.1007/s11045-023-00878-8

This paper proposes a simple and efficient modification to the state-of-the-art zero memory set partitioned embedded block (ZM-SPECK) image coding algorithm to reduce its computational complexity without any significant increase in memory. It has been observed that comparing every element of blocks/sets with the current threshold in every bit-plane is one of the time-consuming process in the ZM-SPECK algorithm. The main contribution of this paper is to avoid this computationally complex process by using the magnitude of the largest coefficient in each subband, which is searched and stored while computing the DWT, prior to the coding. Moreover, the peak-signal-to-noise-ratio (PSNR) of the proposed technique is exactly the same as that obtained by ZM-SPECK. The simulation results show that the proposed method can reduce the complexity of ZM-SPECK by approximately 29% making it suitable for resource-constrained sensor nodes in wireless multimedia sensor networks (WMSNs), Internet of things (IoT), body area networks etc.