Discrete wavelet transform (DWT) is an efficient tool for multi-resolution decomposition of images. It has been shown to be very promising due to its high compression ratio and self-similar data structure. Conventionally a 2-D DWT is accomplished by performing two 1-D operations: one along the rows and the other along the columns of an image. Without executing ordered 1-D transforms, we develop...

The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field due to its rich information about human tasks. In this work EEG waves classification is achieved using the Discrete Wavelet Transform DWT with Fast Fourier Transform (FFT) by adopting the normalized EEG data. The DWT is used as a classifier of the EEG wave’s frequencies, while FFT is impleme...

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...

The compression of still images by means of the Discrete Wavelet Transform (DWT), adopted in the JPEG-2000 and MPEG-4 standards, is becoming more and more widespread because it yields better performances than other compression methods, such as DCT. The demand of efficient architectures for 2-D DWT coding and decoding for a variety of different applications and embedded systems is rapidly increa...

In the computation of forward and inverse Discrete Wavelet Transform (DWT) using Cellular Neural Network (CNN), templates that mimic Haar wavelet are used. It is well known that Daubechies wavelet is the most popular wavelet used in the computation of DWT coefficients. This paper presents an approach towards the design of templates that mimic Daubechies wavelets. A global search algorithm, name...

We propose a novel motion estimation/compensation (ME/MC) method for wavelet-based (in-band) motion compensated temporal filtering (MCTF), with application to low-bitrate video coding. Unlike the conventional in-band MCTF algorithms, which require redundancy to overcome the shift-variance problem of critically sampled (complete) discrete wavelet transforms (DWT), we perform ME/MC steps directly...

Telemedicine is well known application where enormous amount of medical data need to be transferred securely over network and manipulate effectively. Security of digital data, especially medical images, becomes important for many reasons such as confidentiality, authentication and integrity. Digital watermarking has emerged as a advanced technology to enhance the security of digital images. The...

In this paper, the PSNR performance of conventional discrete cosine transform (DCT) OFDM system is compared with discrete wavelet transform (DWT)-OFDM system. We use different error correcting codes viz; Reed Solomon, LDPC, DCT and DWT. KeywordsDCT, DWT, OFDM, Reed Solomon, LDPC.

The Discrete Wavelet Transform (DWT) is a signal processing technique popularised by its results in data compression. Considerable work has been done in designing novel architectures to perform the DWT, including a systolic architecture designed by the authors, but little attention has been given to the inverse DWT which is needed in applications such as data compression for signal reconstructi...