SFrWF: Segmented fractional wavelet filter based Dwt for low memory image coders
Mohd Tausif, Ekram Khan, Mohd Hasan, Martin Reisslein · 2017 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON) · 2017
The Discrete Wavelet Transform (DWT) is extensively used for image coding due to its excellent energy compaction property and its ability to simultaneously analyze images in space-frequency domains. However, conventional methods of computing the DWT coefficients of an image require large amounts of memory, thus making them unsuitable for memory-constraint low-cost portable devices. In this paper we propose a novel low memory approach named Segmented Fractional Wavelet Filter SFrWF to compute the DWT of high resolution images on low-memory devices. Evaluation results show that the SFrWF requires less than 10 kB of RAM for a gray-scale image of size 2048×2048 thus making the SFrWF suitable for low-cost visual sensor nodes.