Lifting Wavelet Transform Research Articles

Reduction of rounding noise and lifting steps in non-separable four-dimensional quadruple lifting integer wavelet transform

The wavelet transform (WT)-based JPEG 2000 is a standard for the compression of digital images that uses a separable lifting structure in which a multidimensional image signal is transformed separately along its horizontal and vertical dimensions. A non-separable three-dimensional (3D) structure is used to minimize the number of lifting steps in existing methods and can reduce the delay between input and output as each process is implemented by cascading in lifting calculation. This structure reduces rounding noise and the number of steps of the lifting scheme in the transform. The non-separable 3D structure in the 5/3-type transform for lossless coding reduces rounding noise, but it increases in the 9/7-type transform for lossy coding in the structure. A combination of 2D and 3D non-separable structures for 4D integer WT has been proposed to solve this problem, but the original filter arrangements need to be preserved to reduce rounding noise. Therefore, in this study, a non-separable 2D structure for the integer implementation of a 4D quadruple lifting WT with a 9/7 filter is proposed. The proposed wavelet transform has the same output signal as the conventional separable structure except for the rounding noise. As the order of the original lifting scheme is preserved, rounding noise in pixels of the decoded image can be significantly reduced, and the upper bounds of quality and lossy decoded 4D medical images can be improved.

Hiding Information Using different lighting Color images

The host medium for the secret message is one of the important principles for the designers of steganography method. In this study, the best color image was studied to carrying any secret image.The steganography approach based Lifting Wavelet Transform (LWT) and Least Significant Bits (LSBs) substitution. The proposed method offers lossless and unnoticeable changes in the contrast carrier color image and imperceptible by human visual system (HVS), especially the host images which was captured in dark lighting conditions. The aim of the study was to study the process of masking the data in colored images with different light intensities. The effect of the masking process was examined on the images that are classified by a minimum distance and the amount of noise and distortion in the image. The histogram and statistical characteristics of the cover image the results showed the efficient use of images taken with different light intensities in hiding data using the least important bit substitution method. This method succeeded in concealing textual data without distorting the original image (low light) Lire developments due to the concealment process.The digital image segmentation technique was used to distinguish small areas with masking. The result is that smooth homogeneous areas are less affected as a result of hiding comparing with high light areas. It is possible to use dark color images to send any secret message between two persons for the purpose of secret communication with good security.

Digital Watermarking using Lifting Wavelet Transform of Crowd Sourced Images

Capturing of digital images through Mobile based e-governance applications are growing day-by-day and issue related to protection of copyrights of digital images has become very critical. Protecting these high-volume geo-tagged time stamped digital images captured through android apps and ensuring that these images are suitable for social audit are key challenge for today’s application development. Digital image watermarking is a process by which secret information can be in digital images so that it is possible to guard copyrights. The paper discusses an efficient digital image watermarking system using lifting wavelet transform. The proposed algorithm aims to minimize distortion of selected watermarked image. The performance of the algorithm has been tested using available images with MATLAB and their results have been properly analyzed with existing methods. The variance value between coefficients of lifting wavelet transform (LFT) in a block with size 2 x 2 has been chosen for embedding the binary watermark and the blocks are also then shuffled randomly. The result of various experiments has demonstrated that the developed algorithm is robust against various types of attacks being applied.

Adaptive Directional Lifting Wavelet Transform VLSI Architecture

This paper presents an efficient VLSI architecture of the 2-D wavelet transform for the adaptive directional lifting (ADL) scheme in image coding. To avoid accumulating errors from irrational wavelet transform coefficients, algebraic integers with appropriate input scaling parameters are used. A two-parallel architecture with zigzag processing of the image stream is used to increase the throughput. In a 45-nm CMOS technology, the synthesis results indicate that the proposed architectures for the Daub-4 and 5/3 wavelets can operate at a clock frequency of about 250 MHz with an estimated throughput of 4 Gb/s.

Image Dehazing Using Dark Channel Prior and Fast Guided Filter in Daubechies Lifting Wavelet Transform Domain

Image Dehazing Using Dark Channel Prior and Fast Guided Filter in Daubechies Lifting Wavelet Transform Domain

Design of high performance copyright protection watermarking based on lifting wavelet transform and bi empirical mode decomposition

This paper developed new and efficient image watermarking scheme for copyright protection based on Lifting wavelet transform (LWT) and Bi- dimensional Empirical Mode Decomposition (BEMD). A LWT has been selected because it is fast, less computational cost and maintains the integrity of the recovered watermark. The BEMD transform can separate the image from the most robust to the least sensitive or fragile frequency bands. This advantage is utilised in this study for the purpose of embedding the watermark in the robust part of BEMD, i.e. the residue (r). In addition, the embedding process has been performed in the low sub-band of LWT decomposed image as the low sub-band is more robust to image processing such as JPEG compression. The robust watermark which is grey scale image is decomposed using DWT to enhance the security and select only high sub-band as it has less impact on the quality of the watermarked image. As a result, the original image’s visual quality can be preserved and the concealed watermark could be successfully retrieved even if the watermarked images have undergone severe attacks like JPEG, rotation, Gamma correction, filtering, additive noise, translation, shearing, and scaling. Furthermore, the improved scheme offers greater robustness against many image processing operations, in comparison to the current schemes about copyright protection.

Synchronous blind audio watermarking via shape configuration of sorted LWT coefficient magnitudes

This study explores the distributive characteristics of wavelet coefficients to enable blind watermarking in audio files. Binary embedding is performed in the low-frequency approximation subband on a frame-by-frame basis after the application of 3-level lifting wavelet transform (LWT). Within each frame, the sorted sequence of the approximation coefficient magnitudes is reshaped according to the intended bit rate of the watermark. A formula regulated by two controlling parameters is presented to carry out sorted sequence reconfiguration (SSR) without perturbing the magnitude order. To cope with time shifting and/or time scaling attacks, the proposed LWT-SSR scheme is further incorporated with an improved synchronization technique for the tracking of frame locations. Embedding strength, as reflected by the signal-to-noise ratio, is controlled at a level near 20 dB while operating at 86.13 bits per second. The objective differences obtained using the PEAQ metric indicate that the resulting watermarked audio signals are perceptually close to the original. Comparison results confirm the robustness of the proposed LWT-SSR against common signal processing operations as well as time-scaling and time-shifting attacks.

Comparative studies of discrete cosine transform and lifting wavelet transform techniques for compression of blood pressure signal in salt sensitive Dahl rat

This paper introduces a study based on quality controlled discrete cosine transform (DCT) and lifting wavelet transform (LWT) based compression method for blood pressure signal compression in salt sensitive Dahl rat. The transformed coefficients are thresholded using the bisection algorithm to match the predefined user specified percentage root mean square difference (PRD) within the tolerance. Then, the binary lookup table is made to store the position map for zero and non-zero coefficients (NZC). The NZC are quantised by Max-Lloyd quantiser followed by arithmetic coding. Lookup table is encoded by Huffman coding. The results are presented on different blood pressure signals of varying characteristic. There is no significant difference in before quantisation PRD (BPRD) and after quantisation PRD (QPRD) in various signals in both transforms. Mean compression ratio increases with an increase in user define PRD (UPRD).

Fault Diagnosis of Bearing by Utilizing LWT‐SPSR‐SVD‐Based RVM with Binary Gravitational Search Algorithm

The fault diagnosis method of bearing based on lifting wavelet transform (LWT)‐self‐adaptive phase space reconstruction (SPSR)‐singular value decomposition (SVD)‐based relevance vector machine (RVM) with binary gravitational search algorithm (BGSA) is presented in this study, among which LWT‐SPSR‐SVD (LSS) is presented for feature extraction of the bearing vibration signal, the dynamic characteristics of lifting wavelet coefficients′ (LWCs′) reconstructed signals of the bearing vibration signal can be reflected by SPSR for LWCs′ reconstructed signals of the bearing vibration signal, and BGSA is used to select the embedding space dimension and time delay of phase space reconstruction (PSR) and kernel parameter of RVM. In order to show the superiority of LWT‐SPSR‐SVD‐based RVM with BGSA (LSS‐BGSA‐RVM), the traditional RVM trained by the training samples with the features based on LWT‐SVD (LS‐RVM) is used to compare with the proposed LSS‐BGSA‐RVM method. The experimental result demonstrates that compared with LS‐RVM, LSS‐BGSA‐RVM can achieve the higher diagnosis accuracy for bearing.

Comparative studies of discrete cosine transform and lifting wavelet transform techniques for compression of blood pressure signal in salt sensitive Dahl rat

This paper introduces a study based on quality controlled discrete cosine transform (DCT) and lifting wavelet transform (LWT) based compression method for blood pressure signal compression in salt sensitive Dahl rat. The transformed coefficients are thresholded using the bisection algorithm to match the predefined user specified percentage root mean square difference (PRD) within the tolerance. Then, the binary lookup table is made to store the position map for zero and non-zero coefficients (NZC). The NZC are quantised by Max-Lloyd quantiser followed by arithmetic coding. Lookup table is encoded by Huffman coding. The results are presented on different blood pressure signals of varying characteristic. There is no significant difference in before quantisation PRD (BPRD) and after quantisation PRD (QPRD) in various signals in both transforms. Mean compression ratio increases with an increase in user define PRD (UPRD).

Enhanced Image Coding Scheme Based on Modified Embedded Zerotree Wavelet Transform (DMEZW)

In this paper the proposed scheme uses different processing methods by applying Integer Lifting Wavelet Transform (ILWT) on gray scale image generating four subband is presented. The low frequency subbands is compressed losslessly by the Developed Modified Embedded Zerotree Wavelet Transform (DMEZW) directly. The high and middle frequency subbands are compressed lossyly by applying first to single stage Vector Quantization (VQ) then to DMEZW, finally generating two vectors ready for entropy coding and it is presented as Arithmetic Coding (AC) to produce a bit stream to be stored or transmitted. The main improvements of DMEZW is done by modifying the scanning strategy of the wavelet coefficients and the quantization threshold. The high and low frequency subbands are manipulated separately. The experimental results show that the developed method can improve the quality of the recovered image and the encoding efficiency. The proposed scheme programming code has achieved high Compression Ratio (CR) and remarkable Peak Signal to Noise Ratio (PSNR).

Multiple-image encryption via lifting wavelet transform and XOR operation based on compressive ghost imaging scheme

A multiple-image encryption method via lifting wavelet transform (LWT) and XOR operation is proposed, which is based on a row scanning compressive ghost imaging scheme. In the encryption process, the scrambling operation is implemented for the sparse images transformed by LWT, then the XOR operation is performed on the scrambled images, and the resulting XOR images are compressed in the row scanning compressive ghost imaging, through which the ciphertext images can be detected by bucket detector arrays. During decryption, the participant who possesses his/her correct key-group, can successfully reconstruct the corresponding plaintext image by measurement key regeneration, compression algorithm reconstruction, XOR operation, sparse images recovery, and inverse LWT (iLWT). Theoretical analysis and numerical simulations validate the feasibility of the proposed method.

A New Approach to Bayesian Change Point Detection Using Lifting Wavelet Transform

A New Approach to Bayesian Change Point Detection Using Lifting Wavelet Transform

Application of Denoising Methods of SINS Data Based on Wavelet Transform

This paper is devoted to the application of data filtering methods based on wavelet transform (WT). The considered methods allow to restore noisy signals of inertial sensors in real time. A comparison of the discrete wavelet transform (DWT) and lifting wavelet transform (LWT) with different wavelet functions, decomposition levels and threshold filtering functions is presented.

On-line deformation monitoring of thin-walled parts based on least square fitting method and lifting wavelet transform

This paper proposed a condition monitoring system using least square fitting method and lifting wavelet transform (LWT) to realize online monitoring of the thin-walled parts’ deformation. Firstly, the overall deformation matrix under LWT method is established. Then, the force signals were transformed by LWT, which were applied to the overall deformation matrix to monitor the machining deformation of the whole parts. The error between monitoring deformation and the actual deformation is within 10 μm through experiment, which verifies the accuracy and practicability of the developed monitoring method.

Volumetric Medical Images Lossy Compression using Stationary Wavelet Transform and Linde-Buzo-Gray Vector Quantization

The aim of the study is to reduce the size required for storage along with decreasing the bitrate and the bandwidth for the process of sending and receiving the image. It also aims to decrease the time required for the process as much as possible. This study proposes a novel system for efficient lossy volumetric medical image compression using Stationary Wavelet Transform and Linde-Buzo-Gray for Vector Quantization. The system makes use of a combination of Linde-Buzo-Gray vector quantization technique for lossy compression along with Arithmetic coding and Huffman coding for lossless compression. The system proposed uses Stationary Wavelet Transform and then compares the results obtained to Discrete Wavelet Transform, Lifting Wavelet Transform and Discrete Cosine Transform at three decomposition levels. The system also compares the results obtained using transforms with only Arithmetic Coding and Huffman Coding for Lossless Compression.The results show that the system proposed outperforms the others.

Geometric distortion correction based robust watermarking scheme in LWT-SVD domain with digital watermark extraction using SVM

With the advent of technology, digital image watermarking turns to be an effective technique to protect digital images from illegal usages and manipulation. In digital image watermarking, one of the major challenges is to provide robustness against geometrical attack maintaining adequate level of imperceptibility and security. In this work, a robust digital image watermarking scheme is proposed based on the combination of lifting wavelet transform(LWT) and singular value decomposition(SVD). To achieve better correlation between the extracted and original watermark, SVM-based binary classification approach is integrated in watermark extraction. In the proposed technique, geometric distortion correction based approach is incorporated with SVM based binary watermark detection to achieve improved robustness against de-synchronization attack. The 3-level LWT is performed on the cover image where horizontal (HL) sub-band is chosen for binary watermark insertion. The training and testing patterns are formed using an optimized set of features along with the singular values of corresponding blocks. In case of de-synchronization attacks, geometrical distortion correction is required before performing watermark extraction. In the detection process, the geometric distortion parameters of the attacked watermarked image are estimated by the geometric correction method. This algorithm provides high robustness against both the geometrical and non-geometrical attacks. It has been observed that the algorithm gives average imperceptibility of ~42.27 dB with the watermark capacity of 512 bits. Experimental results suggest that the proposed watermarking scheme provides significant improvement in terms of robustness and security of the watermark. The subjective analysis also suggests that proposed scheme provides improved performance over some of the recent existing techniques.

LWT–DSR based new robust framework for watermark extraction under intentional attack conditions

This paper proposes a new watermarking approach using dynamic stochastic resonance (DSR) based tuning operation to extract the watermark logo from the watermarked image that has undergone different intentional and signal processing attacks. This method is intended to provide remedies from the shortcomings of the technique proposed by Lin et al. (2008), and invalidates the effect of intentional attacks recently designed by Meerwald et al. (2009). The algorithm incorporates three level image decomposition using lifting wavelet transform (LWT) and low-pass subband is utilized for data hiding purpose. Watermark bits are embedded into the blocks of non-overlapped wavelet coefficients of the cover image by quantizing the two maximum coefficients of the corresponding block. In watermark extraction process, the DSR is applied by performing the tuning operation on coefficient blocks of attacked watermarked image. It is a parameter dependent approach that enhances the performance of watermark extraction, where the parameters of DSR inherently depend on the image properties such as standard deviation or variance. As far as security is concerned, the randomization of wavelet coefficients, blocks, and watermark bits helps the framework to be more secure. The proposed technique is also examined against multiple watermarking attack and successfully proves its authenticity and ownership. Comparison of the proposed technique with recent techniques shows remarkable improvement in terms of robustness and security against various intentional, signal processing, and geometrical attacks.

Efficient and secure cryptosystem for fingerprint images in wavelet domain

In this paper, a fingerprint image encryption algorithm is proposed in order to enhance the protection of fingerprint-based systems against replay attacks. The proposed algorithm is consisting of permutation and diffusion operations in wavelet domain, whereas, one-level Lifting Wavelet Transform Integer-to-Integer is performed to the original fingerprint image. The approximation and detail sub-bands are then partitioned into blocks and permuted using a permutation key. It is noteworthy that, for each sub-band the Rubik’s cube principle is applied. The encrypted image is constructed by ordering the encrypted sub-bands. Eventually, an experimental tests and security analysis were conducted on three fingerprint images attained through Fingerprint Verification Competition “FVC 2000” database. The obtained results confirm the effectiveness of the proposed encryption algorithm and clearly show the robustness against common attacks, for example differential and statistical attacks. In addition, it reveals the high security level achieved.

A predictive model-based image watermarking scheme using Regression Tree and Firefly algorithm

Digital image watermarking has a great importance in the image security nowadays. In this paper, we have proposed a novel robust image watermarking scheme based on combining Regression Tree as a predictive model and Firefly algorithm as a flexible optimization algorithm. In the proposed scheme, Lifting Wavelet Transform as a strong transform domain is employed to separate the host image into four sub-bands and the low frequency sub-band is used to produce non-overlapping blocks. Then, we sort the blocks in ascending order due to the block’s standard derivation. Primary required blocks (owing to the size of watermark image) are used for embedding process, and others used for making Regression Tree. Firefly algorithm is used to optimize multi-scaling factor according to its significant influence in imperceptibility and robustness. For satisfying security aspects, Fibonacci-Q transform is applied to watermark and the bits of resulted scrambled image participated in embedding process. To evaluate the proposed method, it has been investigated by various image processing operations and due to standard metrics, the experimental results are satisfactory.