Nik Shahidah Afifi Taujuddin

Progressive Pixel-to-Pixel Evaluation to Obtain the Hard and Smooth Region for Image Compression

In this paper, we propose a new image compression scheme that is based on the wavelet transform. The image is first divided into 64 × 64 pixels block. The progressive pixel-to-pixel evaluation is done to find the individual pixel intensity in each block. Then the different value between the maximum pixel intensity value and the minimum pixel intensity value is calculated. This value will lead to a special representation of each where the block with high difference value is set as the hard region block while the block with low difference value is set as the smooth region block. This region will be decomposed individually using Discrete Wavelet Transform (DWT) and thresholded using different threshold method based on the block characteristic. The proposed method shows compression did well on image with a large smooth area.

Enhancement of Medical Image Compression by Using Threshold Predicting Wavelet-Based Algorithm

In recent decades with the rapid development in biomedical engineering, digital medical images have been becoming increasingly important in hospitals and clinical environment. Apparently, traversing medical images between hospitals need a complicated process. Many techniques have been developed to resolve these problems. Compressing an image will reduce the amount of redundant data with the good quality of the reproduced image sufficiently high, depending on the application. In the case of medical images, it is important to reproduce the image close to the original image so that even the smallest details are readable. The aim of this paper is to propose a new compression algorithm by using the threshold values. It started by segmenting the image area into Region of Interest (ROI) and Region of Background (ROB) and use the special features provide by wavelet algorithm to produce efficient coefficients. These coefficients are then will be used as threshold value in our new proposed thresholding predicting for compression algorithm. The new compression algorithm is expected to produce a fast compression algorithm besides decreasing the image size without tolerating with the precision of image quality.

Image compression using a new adaptive standard deviation thresholding estimation at the wavelet details subbands

The process before quantization stage in compression process is a very crucial stage espeacially in application that require a high compression ratios. So, in this paper, we propose a new method of image compression that is based on reducing the wavelet coefficients in wavelet details subbands. It is based on the concept of local subband wavelet coefficients minimization to find the optimum threshold value for wavelet coefficients in each detail subbands. The proposed method decomposed the image into LL (low resolution approximate image), HL (intensity variation along column, horizontal edge), LH (intensity variation along row, vertical edge) and HH (intensity variation along diagonal). The coefficients in details subband retrived from the decomposition process is then manipulated in such a way that the nearly zero coefficient is discarded while the rest is remained. This process will reduce the unsignificant wavelet coefficient that leads to a great compression ratio while preserving the informative data to produce a good image quality as can be seen in the experiment done.

Secured MyVirtualPDA using advanced encryption standard

One of the most useful features in any personal digital assistant (PDA) is that it can accumulate information needed including easy-to-forget details. Some of the information stored is likely to be very sensitive including credit card numbers, personal identification, and passwords. To protect this sensitive data, most PDAs offer password protection as a basic authentication. However, to rely on this type of protection alone is not enough. As the writing of secret message cryptography, also known as science and mathematical lock and key (Schafer, 2003), evolved people rely on the encryption process to increase their level of data protection.