We present an algorithm that compresses two-dimensional data arrays, which are piece-wise smooth in one direction and have oscillatory events in the other direction. Seismic and hyperspectral data have this mixed structure. The transform part of the compression process is an algorithm that combines wavelet and the local cosine transform (LCT). The quantization and the entropy coding parts in th...

As digital images are often in compressed forms, image retrieval involves full decoding of images prior to feature extraction. The decoding process can be computation-expensive so feature extraction in compressed domain is desired. In this work, wavelet-based features are extracted as unified features for retrieval of JPEG and JPEG2000 images. A fast algorithm is proposed to approximately trans...

We propose a novel face recognition using Dual Tree Complex Wavelet Transform (DTCWT), which is used to extract features from face images. The Complex Wavelet Transform is a tool that uses a dual tree of wavelet filters to find the real and imaginary parts of complex wavelet coefficients. The DT-CWT is, however, less redundant and computationally efficient. CWT is a relatively recent enhancemen...

Gabor frames, especially digital Gabor filters, have long been known as indispensable tools for local time-frequency analysis of discrete signals. With strong orientation selectivity, tensor products discrete (tight) Gabor frames also see their applications in image analysis and restoration. However, the lack of multi-scale structures existing in MRA-based wavelet (tight) frames makes discrete ...

In this paper we propose a new steganography technique which embeds secrete color image into color cover work in frequency domain. Unlike the spatial domain approach, secrete image or data are embedded in the low frequency coefficients resulted from Discrete Wavelet Transform, as it is much sensitive to Human Visual System several researchers are not preferring to embed data in low frequency co...

One of the advantages of the Discrete Wavelet Transform (DWT) compared to Fourier Transform (e.g. Discrete Cosine Transform DCT) is its ability to provide both spatial and frequency localization of image energy. However, WT coefficients, like DCT coefficients, are defined by magnitude as well as sign. While algorithms exist for the coding of wavelet coefficients magnitude, there are no efficien...

Unlike Fourier basis which constitutes fixed sine and cosine waves; the Wavelet Transform has infinite basis functions. The choice of good basis is application dependent. Statistical parameters of the image are dynamic and differ from image to image. A moment vector of natural image will be different from the moment vector of synthetic image. Similarly the edges in natural image have structural...

Non-blind watermarking is a form of with watermark image validation process that requires host image. The use the transform domain more robust and imperceptible. method resistant to various forms digital attacks. In this study, Discrete Cosine Transform (DCT) Wavelet (DWT) were selected as insertion algorithms. DCT faster attacks, especially in compression but has lower imperceptibility than DW...

In this paper, comparison of three Video compression techniques i.e. Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Hybrid is done. DCT is applied to Rows, Columns and Rows*Columns separately to frames in a video with compression factor of 2, 4 and 8, whereas Discrete Wavelet Transform(DWT) is applied till 2 level of DWT decomposition and Hybrid-1 combining DCT and DWT 1 ...