High-Performance FPGA Implementation of Discrete Wavelet Transform for Image Processing Abstract: In this paper, two high-performance FPGA implementations of discrete wavelet transform (DWT) and ...

Apply a discrete wavelet transform on input noisy image (AWGN with zero mean and standard deviation of) to get noisy coefficients. Then, we can set the parameters of the optimization algorithm (number ...

The Discrete Wavelet Transform (DWT) has gained the reputation of being a very effective signal analysis tool for many practical applications. This paper presents an approach towards VLSI ...

Lifting-Based Discrete Wavelet Transform Architectures Publication Trend The graph below shows the total number of publications each year in Lifting-Based Discrete Wavelet Transform Architectures.

Therefore, image noise reduction processing is necessary to obtain higher-quality images. For the characteristics of its multi-analysis, relativity removal, low entropy, and flexible bases, the ...

Noise is a major factor in degrading the image quality of various medical images (MRI, CT scan, Ultrasound etc.). Speckle noise is a most common noise presents in all medical images including ...

In this study, we propose a vision transformer (ViT) model with two-stage fine-tuning using wavelet transformation to improve classification performance. In the first stage, feature extraction is ...

Denoising is essential before applying further processing tasks like segmentation or classification. This work demonstrates how discrete wavelet transform (DWT) can decompose an image into different ...

Although a wavelet transform has decorrelating properties, structures in images, like edges, are never decorrelated completely, and these structures appear in the wavelet coefficients: a ...