Simple Signal Extension Method for Discrete Wavelet Transform

Discrete wavelet transform of finite-length signals must necessarily handle the signal boundaries. The state-of-the-art approaches treat such boundaries in a complicated and inflexible way, using special prolog or epilog phases. This holds true in particular for images decomposed into a number of scales, exemplary in JPEG 2000 coding system. In this paper, the state-of-the-art approaches are extended to perform the treatment using a compact streaming core, possibly in multi-scale fashion. We present the core focused on CDF 5/3 wavelet and the symmetric border extension method, both employed in the JPEG 2000. As a result of our work, every input sample is visited only once, while the results are produced immediately, i.e. without buffering.Comment: preprint; presented on ICSIP 201

Design of wireless swallowable capsule with minimum power consumption and high resolution images

Medical technology has undergone major breakthroughs in recent years, especially in the area of the examination tools for diagnostic purposes. The traditional examination method for the diagnosis of gastrointestinal diseases is gastroscopy with the use of an endoscope. Wireless camera pill has created a new perspective for engineers and physicians. After years of great innovation, commercial swallowable pills have been produced and applied in clinical practice. These pills can cover the examination of the gastrointestinal system and provide to the physicians not only a lot more useful data that is not available from the traditional methods, but also elimination of the use of the painful endoscopy procedure. In this paper, a new design of the wireless swallowable pills has been proposed. It takes advantage of the benefits of every sub-system, like camera lenses, image compressor and RF sub-system. In this way our system can provide enough and accurate data to the physicians

A Vlsi architecture for lifting-based wavelet packet transform in fingerprint image compression

FBI uses a technique called Wavelet Scalar Quantization (WSQ), a wavelet packet transform (WPT) based method, to compress its fingerprint images. Though many VLSI architectures have been proposed for wavelet transform in the literature, it is not the case for the WPT. In this thesis, a VLSI architecture capable of computing the WPT is presented for application of WSQ. In the proposed architecture, Lifting Scheme (LS) is used to generate wavelets instead of the traditional convolution filter-bank (FB) specified in original standard. A comparative study between LS and FB shows that quality of images transformed by LS is completely acceptable (with 30dB∼40dB PSNR at a target bit rate of 0.75dpp) while fewer operations required. In particular, to compare with FB, the hardware consumption, for our WSQ application, is reduced to half due to the LS. Moreover, this architecture can be easily configured to compute any required WPT application

Lossless and low-cost integer-based lifting wavelet transform

Discrete wavelet transform (DWT) is a powerful tool for analyzing real-time signals, including aperiodic, irregular, noisy, and transient data, because of its capability to explore signals in both the frequency- and time-domain in different resolutions. For this reason, they are used extensively in a wide number of applications in image and signal processing. Despite the wide usage, the implementation of the wavelet transform is usually lossy or computationally complex, and it requires expensive hardware. However, in many applications, such as medical diagnosis, reversible data-hiding, and critical satellite data, lossless implementation of the wavelet transform is desirable. It is also important to have more hardware-friendly implementations due to its recent inclusion in signal processing modules in system-on-chips (SoCs). To address the need, this research work provides a generalized implementation of a wavelet transform using an integer-based lifting method to produce lossless and low-cost architecture while maintaining the performance close to the original wavelets. In order to achieve a general implementation method for all orthogonal and biorthogonal wavelets, the Daubechies wavelet family has been utilized at first since it is one of the most widely used wavelets and based on a systematic method of construction of compact support orthogonal wavelets. Though the first two phases of this work are for Daubechies wavelets, they can be generalized in order to apply to other wavelets as well. Subsequently, some techniques used in the primary works have been adopted and the critical issues for achieving general lossless implementation have solved to propose a general lossless method. The research work presented here can be divided into several phases. In the first phase, low-cost architectures of the Daubechies-4 (D4) and Daubechies-6 (D6) wavelets have been derived by applying the integer-polynomial mapping. A lifting architecture has been used which reduces the cost by a half compared to the conventional convolution-based approach. The application of integer-polynomial mapping (IPM) of the polynomial filter coefficient with a floating-point value further decreases the complexity and reduces the loss in signal reconstruction. Also, the “resource sharing” between lifting steps results in a further reduction in implementation costs and near-lossless data reconstruction. In the second phase, a completely lossless or error-free architecture has been proposed for the Daubechies-8 (D8) wavelet. Several lifting variants have been derived for the same wavelet, the integer mapping has been applied, and the best variant is determined in terms of performance, using entropy and transform coding gain. Then a theory has been derived regarding the impact of scaling steps on the transform coding gain (GT). The approach results in the lowest cost lossless architecture of the D8 in the literature, to the best of our knowledge. The proposed approach may be applied to other orthogonal wavelets, including biorthogonal ones to achieve higher performance. In the final phase, a general algorithm has been proposed to implement the original filter coefficients expressed by a polyphase matrix into a more efficient lifting structure. This is done by using modified factorization, so that the factorized polyphase matrix does not include the lossy scaling step like the conventional lifting method. This general technique has been applied on some widely used orthogonal and biorthogonal wavelets and its advantages have been discussed. Since the discrete wavelet transform is used in a vast number of applications, the proposed algorithms can be utilized in those cases to achieve lossless, low-cost, and hardware-friendly architectures

Low-Complexity 3D-DWT video encoder applicable to IPTV

3D-DWT encoders are good candidates for applications like professional video editing, IPTV video surveillance, live event IPTV broadcast, multispectral satellite imaging, HQ video delivery, etc., where a frame must be reconstructed as fast as possible. However, the main drawback of the algorithms that compute the 3D-DWT is the huge memory requirement in practical implementations. In this paper, and in order to considerably reduce the memory requirements of this kind of video encoders, we present a new 3D-DWT video encoder based on (a) the use of a novel frame-based 3D-DWT transform that avoids video sequence partitioning in Groups Of Pictures (GOP) and (b) a very fast run-length encoder. Furthermore, an exhaustive evaluation of the proposed encoder (3D-RLW) has been performed, analyzing the sensibility of the ¿lters employed in the 3D-DWT transform and comparing the evaluation results with other video encoders in terms of R/D, coding/decoding delay and memory consumptionThanks to Spanish Ministry of Education and Science under grants DPI2007-66796-C03-03 for funding.López ., O.; Piñol ., P.; Martinez Rach, MO.; Perez Malumbres, MJ.; Oliver Gil, JS. (2011). Low-Complexity 3D-DWT video encoder applicable to IPTV. Signal Processing: Image Communication. 26(7):358-369. https://doi.org/10.1016/j.image.2011.01.008S35836926

Discrete Wavelet Transformation Implementation in GPU through Register Based Strategy

The significant architectural changes made by Nvidia during the launch of Kepler architecture in 2012, upgraded its GPUs with greater register memory and rich instructions set to have communication between registers through available threads. This created a potential for new programming approach which uses registers for sharing and reusing of data in the context of the shared memory. This kind of approach can considerably improve the performance of applications which reuses implied data heavily. This work is based upon of register-based implementation of the Discrete Wavelet Transform (DWT) with the help of CUDA and openCV. DWT is the data decorrelation approach in the area of video and image coding. Results of this particular approach indicate that this technique performs at least four times better than the best GPU implementation of the DWT in past. Experimental tests also prove that this approach shows the performance close to the GPUs performance limits