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Wavelet Transform for Image Coding: JPEG2000
Published in Yun-Qing Shi, Huifang Sun, Image and Video Compression for Multimedia Engineering, 2019
In this section, we summarize the advantages possessed by lifting scheme. Because of these merits, lifting scheme has been adopted by JPEG2000 (Rabbani 2001). Lifting scheme provides a different way to illustrate wavelet transform. It is noted that most of wavelet transform theory starts from Fourier transform theory. Lifting scheme, however, does provide one way to view wavelet transform without using Fourier transform.Lifting scheme is simple and hence efficient in implementation.In addition, lifting scheme can reduce memory requirement significantly. It can provide so-called in-place computation of wavelet coefficients. That is, it can overwrite the memory used to store input data with wavelet coefficients. This bears similarity to the FFT.Lifting scheme lends itself easily to IWT computation.
Perceptual Video Quality Metrics — A Review
Published in H.R. Wu, K.R. Rao, Digital Video Image Quality and Perceptual Coding, 2017
Multi-Channel Decomposition: It is widely accepted that the HVS bases its perception on multiple channels which are tuned to different ranges of spatial frequencies and orientations. Measurements of the receptive fields of simple cells in the primary visual cortex revealed that these channels exhibit approximately a dyadic structure [Dau80]. This behavior is well matched by a multi-resolution filter bank or a wavelet decomposition. An example for the former is the cortex transform [Wat87], a flexible multi-resolution pyramid, whose filters can be adjusted within a broad range. Wavelet transforms on the other hand offer the advantage that they can be implemented in a computationally efficient manner by a lifting scheme [DS98].
A novel design of low-cost hearing aid devices using an efficient lifting filter bank with a modified variable filter
Published in Expert Review of Medical Devices, 2022
N Subbulakshmi, R Manimegalai, G Rajakumar, T Ananth Kumar, Umadevi Kosuri
The lifting scheme has been continuously implemented for generating second-generation wavelet transform with advanced technology. The use of hearing aid applications in digital signal processing (DSP) algorithms has been a significant field of research. The emerging field of signal processing phenomena improves the hearing aid design as a consecutive process [1]. It is proven that predictable designs are invented, and more revolutions will be occurred in hearing aid device technology’s cutting-edge future [2]. The core part of the hearing aid device is the filter bank since it occupies more design space and consumes maximum power. A lifting scheme methodology is proposed in order to address the issues of power consumption and the area. In the biorthogonal wavelet [3,4], Cohen–Daubaches–Feauveau (CDF) reiterates a subclass whose scaling parameter is symmetrical. This CDF technique is instigated with the lifting scheme method. Some of them are listed in the following: Cubic, Haar, Daubechies-4 series and CDF like Daub-16 [5], Daub-12, Daub-10, Daub-8, Daub-6, and Daub-4. The following are the biorthogonal CDF classifications: (i) CDF (9,7); (ii) CDF (7,5); and (iii) CDF (5,3).
Optimal blind colour image watermarking based on adaptive chaotic grasshopper optimization algorithm
Published in The Imaging Science Journal, 2022
Digital watermarking methods fall into two general classifications, namely Spatial and Frequency Domain Watermarking. In the spatial watermarking domain, the pixel values of the host image are changed directly to embed watermark. The frequency domain method embeds the watermark in the transformed coefficients of the host image. The recently used transforms are Fourier Transform [6], Hadamard Transform [7], Discrete Cosine Transform (DCT) [8], Lifting Wavelet Transform (LWT) [9], Discrete Wavelet Transform (DWT) [10], Walsh Hadamard Transform [11] and Hybrid Transform [12–14]. LWT is an efficient wavelet of the second generation which is also known as the Lifting Scheme. This frequency domain watermarking method [15] is preferrable than the spatial domain watermarking because it reveals strong transparency and robustness.
An Overview of Digital Audio Steganography
Published in IETE Technical Review, 2020
Hrishikesh Dutta, Rohan Kumar Das, Sukumar Nandi, S. R. Mahadeva Prasanna
A problem with the simple wavelet domain steganography, as seen in the previous part of this section, is that on applying those wavelets on an integer signal such as speech, the resultant coefficients are not integers. Thus, these techniques scale the resultant coefficients and then convert these coefficients into a binary sequence, which results in some errors. To resolve this issue, lifting scheme is used to obtain Int2Int wavelets [76]. Lifting scheme is a technique that designs the wavelet as well as performs DWT. The Int2Int denotes that wavelet coefficients for an integer input signal are also integer and hence scaling of coefficients is not required. The error in the embedding procedure is negligible in this case.