Roger L. Claypoole, Jr. and Richard G. Baraniuk, Rice University Summary We introduce and discuss biorthogonal wavelet transforms using the lifting construction. The lifting construction exploits a spatial{domain, prediction{error interpretation of the wavelet transform and provides a powerful framework for designing customized transforms. We discuss the application of lifting to adaptive and n...

Description of signals using wavelet transforms leads to useful time-frequency localization and possible signal compression. Based on the Discrete Wavelet Transform (DWT) an adaptive sampling algorithm in the discrete time domain is constructed, by finding an univocal relation between the signal’s samples and the non-zero transform coefficients of its DWT. Reconstruction is performed through re...

This paper describes a super-resolution technique based on interpolation of the high-frequency subband images obtained by discrete wavelet transform (DWT) and the input image. This technique uses DWT to decompose an image into different subband images. Then the high-frequency subband images and the low-resolution input image have been interpolated, followed by combining all these images to gene...

This paper discussed an improvement algorithm of image digital watermarking based on the discrete wavelet transform (DWT) and singular value decomposition (SVD). In this algorithm, a good characteristic of multiresolution and time-frequency local analysis of discrete wavelet transform combining with image intrinsic algebraic properties of SVD. After decomposing the original host image into four...

This paper proposes a hardware-efficient architecture design of wavelet-based adaptive visible watermarking. Our method adopts discrete wavelet transform (DWT) to embed visible watermarking. We perform this algorithm using hardware-efficient architectures that combine operational reduction and resource sharing techniques. Our method provides high quality visible watermarking image and small har...

The advantages of the wavelet transform over conventional transforms, such as the Fourier transform, are now well recognized. Because of its excellent locality in time-frequency domain, wavelet transform is remarkable and extensively used for signal analysis, compressing and denoising. Defining DWT by Mallat [1] provided possibility of its digitally hardware or software implementation. The disc...

Two-dimensional discrete wavelet transform (DWT) for processing image is conventionally designed by line-based architectures, which are simple and have low complexity. However, they suffer from two main shortcomings the memory required for storing intermediate data and the long latency of computing wavelet coefficients. This work presents a new block-based architecture for computing lifting-bas...

Although the discretized continuous wavelet transform enables the computation of the continuous wavelet transform by computers, it is not a true discrete transform. As a matter of fact, the wavelet series is simply a sampled version of the CWT, and the information it provides is highly redundant as far as the reconstruction of the signal is concerned. This redundancy, on the other hand, require...

In this paper, a new method for handwritten signature identification based on rotated complex wavelet filters is proposed. We have proposed to use the rotated complex wavelet filters (RCWF) and dual tree complex wavelet transform(DTCWT) together to derive signature feature extraction, which captures information in twelve different directions. In identification phase, Canberra distance measure i...

In deep networks, the lost data details significantly degrade performances of image segmentation. this paper, we propose to apply Discrete Wavelet Transform (DWT) extract during feature map down-sampling, and adopt Inverse DWT (IDWT) with extracted up-sampling recover details. On popular segmentation U-Net, SegNet, DeepLabV3+, design wavelet integrated networks for (WaveSNets). Due effectivenes...