This paper proposes a feature selection based classification method that can be applied to better accuracy in the Digital Radiographs (DR) for the identification of Inferior Alveolar Nerve Injury (IANI). Different conventional features based on the shape and EZW (Embedded Zero tree Wavelet) based texture features are extracted using different feature extraction techniques. Then, aggregate votin...

Wideband Multicarrier code division multiple access (MCCDMA) and Rake receivers for wavelet video transmission with four levels of unequal error protection (UEP) codes over additive white Gaussian noise (AWGN) and Rayleigh fading channels are performed and evaluated. The deployment of Wavelets has approached a powerful technique and high quality for compressing video sequence. A spatially scala...

Most hospitals store medical image data in digital form using picture archiving and communication systems due to extensive data digitization of data and increasing telemedicine use. Data storage needs and bandwidth requirements have necessitated use of lossy compression techniques. Wavelet transforms successful use in image compression was extensively studied in literature. Image segmentation a...

The Analytic Hierarchy Process (AHP) has been successfully used in the past for the selection of components, as presented in case studies in the literature. In this paper, an empirical study using AHP to rank components is presented. The components used in the study are for data compression; each implements one of the Arithmetic Encoding (AREC), Huffman coding (HUFF), Burrows-Wheeler Transform ...

Performance analysis of multilevel unequal error protection (UEP) codes with wavelet video compression for wideband code division multiple access (W-CDMA) over additive white Gaussian noise (AWGN) and Rayleigh fading channels are achieved and evaluated. Wavelets possess a dominant method and high quality for compressing video sequence. A spatially scalable video coding framework of MPEG2 in whi...

Medical image compression is an important area of research which aims at producing algorithms that reduce file size and at the same time maintain relevant diagnostic information. The main focus of this paper is to analyze techniques and find a compression scheme that can compress medical images quickly and reduce compression rate while maintaining a good level of visual quality. A Region Of Int...

Compressing an image is significantly different than compressing raw binary data. For this different compression algorithm are used to compress images. Fractal image compression (FIC) has been widely used to compress the image. Apart from FIC, their also exist another algorithm well known as Discrete Wavelet Transform (DWT). Wavelet transform are very powerful compared to other transform becaus...

This paper is aimed at analyzing the performance of three different state-of-the-art image compression schemes namely Embedded Zerotree Wavelet (EZW), Spatial-orientation Trees Wavelet (STW) and Set Partitioning in Hierarchical Trees (SPHIT). The paper analyses the compression schemes using X-ray image data such that the quality of the reconstructed image would be closely related to its origina...

Wavelet based embedded coders such as EZW and SPIHT require full wavelet transform of the image to be buffered for coding. Further, since the transform coefficients are required to be stored in high precision, the buffering requirements are prohibitively high for large images, such as remote sensing images, space borne images, medical images etc. In this paper we investigate, embedded coding of...

We describe a blind watermarking technique for digital images. Our technique constructs an image-dependent watermark in the discrete wavelet transform (DWT) domain and inserts the watermark in the most significant coefficients of the image. The watermarked coefficients are determined by using the hierarchical tree structure induced by the DWT, similar in concept to embedded zerotree wavelet (EZ...