The usage of linear transformations has great relevance for data decorrelation applications, like image and video compression. In that sense, the discrete Tchebichef transform (DTT) possesses useful coding and decorrelation properties. The DTT transform kernel does not depend on the input data and fast algorithms can be developed to real-time applications. However, the DTT fast algorithm presented in literature possess high computational complexity. In this paper, we introduce a new low-complexity approximation for the DTT. The fast algorithm of the proposed transform is multiplication free and requires a reduced number of additions and bit-shifting operations. Image and video compression simulations in popular standards show good performance of the proposed transform. Regarding hardware resource consumption for FPGA shows a 43.1% reduction in configurable logic blocks and ASIC place and route realization shows a 57.7% reduction in the area-time figure compared with the 2D version of the exact DTT.

Low-Complexity Image and Video Coding Based on an Approximate Discrete Tchebichef Transform

Early analysis of resource consumption patterns in mobile applications

Everyday, an enormous number of medical images are produced by hospitals and medical imaging center for research, surgical and disease diagnostics. Therefore, compression is necessary for storing, managing and transferring these data to make storage manageable. Medical images have some parts which are more important called region of interest (ROI) with useful information for the diagnostic purpose that should be reconstructed with high quality during the image decompression process. In this paper, a state-of-the-art image compression format known as Better Portable Graphics (BPG), which is based on the High Efficiency Video Coding (HEVC), is used for medical image compression. In the proposed compression method, first the medical image is segmented into two parts: ROI and non-ROI regions. In the next step, lossless BPG compression algorithm is applied to the ROI areas, and lossy BPG is utilized for non-ROI regions. In the end, the resulting reconstructed images are combined to create a complete compressed image. The MRI scan dataset hosted by the University of Cyprus is used to evaluate the performance of the proposed compression method to demonstrate improvement between 10–25% in the compression rate compared to traditional image compression techniques used in the medical industry.

Medical image compression based on region of interest using better portable graphics (BPG)

3D Tele-Immersion (3DTI) has emerged as an efficient environment for virtual interactions and collaborations in a variety of fields like rehabilitation, education, gaming, etc. In 3DTI, geographically distributed users are captured using multiple cameras and immersed in a single virtual environment. The quality of experience depends on the available network bandwidth, quality of the 3D model generated and the time taken for rendering. In a collaborative environment, achieving high quality, high frame rate rendering by transmitting data to multiple sites having different bandwidth is challenging. In this paper we introduce a network adaptive textured mesh generation scheme to transmit varying quality data based on the available bandwidth. To reduce the volume of information transmitted, a visual quality based vertex selection approach is used to generate a sparse representation of the user. This sparse representation is then transmitted to the receiver side where a sweep-line based technique is used to generate a 3D mesh of the user. High visual quality is maintained by transmitting a high resolution texture image compressed using a lossy compression algorithm. In our studies users were unable to notice visual quality variations of the rendered 3D model even at 90% compression.

Network Adaptive Textured Mesh Generation for Collaborative 3D Tele-Immersion

A standard interchangeable data format was recently developed through the Transportation Pooled-Fund Study TPF-5(299) to meet different requirements and needs for two- and three-dimensional...

Evaluation of Compression Algorithms for 3D Pavement Image Data

This paper presents an efficient image compression approach based on JPEG image compression. JPEG is the most frequently applied image compression technique in today"s world. We have developed an application based on VB.NET for converting and compressing images in JPEG format. Using this application we finally propose a relation between image quality with the amount of image compression.

Shree Mata

Papers

Image Compression and Quality Factor in case of JPEG Image format