A block-based JPEG-LS compression technique with lossless region of interest

2018 ◽  
Author(s):  
Shoukui Yao ◽  
Lihua Deng ◽  
Zhenghua Huang
Keyword(s):  
Region Of Interest ◽  
Compression Technique ◽  
Block Based

Quantization Encoding Algorithm Based Satellite Image Compression

2017 ◽  
Vol 8 (3) ◽  
pp. 740
Author(s):  
Anand M ◽  
V. Mathivananr
Keyword(s):  
Image Compression ◽  
Satellite Images ◽  
Satellite Image ◽  
Region Of Interest ◽  
Digital Data ◽  
Storage Space ◽  
Compression Process ◽  
Compression Technique ◽  
Transmission Bandwidth ◽  
Image Technique

In the field of digital data there is a demand in bandwidth for the transmission of the videos and images all over the worlds. So in order to reduce the storage space in the field of image applications there is need for the image compression process with lesser transmission bandwidth. So in this paper we are proposing a new image compression technique for the compression of the satellite images by using the Region of Interest (ROI) based on the lossy image technique called the Quantization encoding algorithm for the compression. The performance of our method can be evaluated and analyzing the PSNR values of the output images.

scholarly journals Medical Image Watermarking Technique for Accurate Tamper Detection in ROI and Exact Recovery of ROI

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
R. Eswaraiah ◽  
E. Sreenivasa Reddy
Keyword(s):  
Medical Image ◽  
Medical Images ◽  
Image Watermarking ◽  
Region Of Interest ◽  
Tamper Detection ◽  
High Quality ◽  
Medical Image Watermarking ◽  
Block Based ◽  
Embedding Distortion

In telemedicine while transferring medical images tampers may be introduced. Before making any diagnostic decisions, the integrity of region of interest (ROI) of the received medical image must be verified to avoid misdiagnosis. In this paper, we propose a novel fragile block based medical image watermarking technique to avoid embedding distortion inside ROI, verify integrity of ROI, detect accurately the tampered blocks inside ROI, and recover the original ROI with zero loss. In this proposed method, the medical image is segmented into three sets of pixels: ROI pixels, region of noninterest (RONI) pixels, and border pixels. Then, authentication data and information of ROI are embedded in border pixels. Recovery data of ROI is embedded into RONI. Results of experiments conducted on a number of medical images reveal that the proposed method produces high quality watermarked medical images, identifies the presence of tampers inside ROI with 100% accuracy, and recovers the original ROI without any loss.

scholarly journals Block based image compression technique using rank reduction and wavelet difference reduction

2015 ◽  
Author(s):  
Anastasia Bolotnikova ◽  
Pejman Rasti ◽  
Andres Traumann ◽  
Iiris Lusi ◽  
Morteza Daneshmand ◽  
...  
Keyword(s):  
Image Compression ◽  
Rank Reduction ◽  
Compression Technique ◽  
Block Based

scholarly journals Compression of MRI brain images based on automatic extraction of tumor region

2021 ◽  
Vol 11 (5) ◽  
pp. 3964
Author(s):  
Prakash Tunga P. ◽  
Vipula Singh
Keyword(s):  
Brain Magnetic Resonance Imaging ◽  
Region Of Interest ◽  
Set Partitioning ◽  
Arithmetic Coding ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Automatic Extraction ◽  
Performance Parameters ◽  
Compression Technique ◽  
Tumor Region

In the compression of medical images, region of interest (ROI) based techniques seem to be promising, as they can result in high compression ratios while maintaining the quality of region of diagnostic importance, the ROI, when image is reconstructed. In this article, we propose a set-up for compression of brain magnetic resonance imaging (MRI) images based on automatic extraction of tumor. Our approach is to first separate the tumor, the ROI in our case, from brain image, using support vector machine (SVM) classification and region extraction step. Then, tumor region (ROI) is compressed using Arithmetic coding, a lossless compression technique. The non-tumorous region, non-region of interest (NROI), is compressed using a lossy compression technique formed by a combination of discrete wavelet transform (DWT), set partitioning in hierarchical trees (SPIHT) and arithmetic coding (AC). The classification performance parameters, like, dice coefficient, sensitivity, positive predictive value and accuracy are tabulated. In the case of compression, we report, performance parameters like mean square error and peak signal to noise ratio for a given set of bits per pixel (bpp) values. We found that the compression scheme considered in our setup gives promising results as compared to other schemes.

FPGA-Based ROI Encoding for HEVC Video Bitrate Reduction

2020 ◽  
Vol 29 (11) ◽  
pp. 2050182
Author(s):  
Zhilei Chai ◽  
Shen Li ◽  
Qunfang He ◽  
Mingsong Chen ◽  
Wenjie Chen
Keyword(s):  
Data Storage ◽  
Video Compression ◽  
High Efficiency ◽  
Video Quality ◽  
Region Of Interest ◽  
Absolute Difference ◽  
High Efficiency Video Coding ◽  
High Definition ◽  
Mapping Algorithm ◽  
Block Based

The explosive growth of video applications has produced great challenges for data storage and transmission. In this paper, we propose a new ROI (region of interest) encoding solution to accelerate the processing and reduce the bitrate based on the latest video compression standard H.265/HEVC (High-Efficiency Video Coding). The traditional ROI extraction mapping algorithm uses pixel-based Gaussian background modeling (GBM), which requires a large number of complex floating-point calculations. Instead, we propose a block-based GBM to set up the background, which is in accord with the block division of HEVC. Then, we use the SAD (sum of absolute difference) rule to separate the foreground block from the background block, and these blocks are mapped into the coding tree unit (CTU) of HEVC. Moreover, the quantization parameter (QP) is adjusted according to the distortion rate automatically. The experimental results show that the processing speed on FPGA has reached a real-time level of 22 FPS (frames per second) for full high-definition videos ([Formula: see text]), and the bitrate is reduced by 10% on average with stable video quality.

An improved medical image compression technique with lossless region of interest

Optik ◽  
2015 ◽  
Vol 126 (21) ◽  
pp. 2825-2831 ◽  
Author(s):  
Zhiyong Zuo ◽  
Xia Lan ◽  
Lihua Deng ◽  
Shoukui Yao ◽  
Xiaoping Wang
Keyword(s):  
Image Compression ◽  
Medical Image ◽  
Region Of Interest ◽  
Compression Technique ◽  
Medical Image Compression

scholarly journals A novel approach to medical image watermarking for tamper detection and recovery of region of interest using block compression and checksum

2018 ◽  
Vol 7 (4) ◽  
pp. 2137 ◽  
Author(s):  
Gangadhara Rao K ◽  
Chaitanya Konda
Keyword(s):  
Medical Image ◽  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Region Of Interest ◽  
Ultra Sound ◽  
Compression Technique ◽  
Public Network ◽  
Medical Image Watermarking ◽  
Novel Approach ◽  
Effective Use

Effective use of telecommunication and information technology in telemedicine increases the medical services to the patients who are from far away locations. The doctors provide these services by evaluating the patient details & scans like CT Scan, MRI and Ultra Sound. The patient information is exchanged between doctors and patients on a public network which is not safe. In medical image, specific regions are very important to diagnosis known as Region of Interest (ROI) and the rest of the regions are not of much importance known as Region of Non-Interest (RONI). Providing security to the ROI is an important issue hence medical image watermarking is used to transmit the medical images by embedding the ROI into RONI. At the destination, if tampering is found in ROI then recovery of ROI is possible by extracting the ROI from RONI. In the proposed method, the medical image is divided into three parts: BORDER, ROI and RONI. Further the ROI and RONI are divided into blocks and each ROI block is mapped to RONI block by applying division hash function. Lossless block compression technique is applied to each ROI block and embedded the compressed ROI block into mapped RONI block. To provide authenticity to ROI, checksum is calculated for ROI and embed this checksum in BORDER. Again checksum is calculated for each ROI block and placed in mapped RONI blocks. Whether ROI is tampered or not, is to be identified by extracting the checksum from BORDER and if it is tampered then recover the ROI by mapped RONI. The efficiency of the proposed algorithm is estimated by the performance measures mainly Peak Signal to Noise Ratio (PSNR). The proposed method gives good results on average 55 dB of PSNR compared to the previous methods [21] by efficiently compressing the ROI and by checking the authenticity.

A technique for protecting delicate specimens during processing

1989 ◽  
Vol 47 ◽  
pp. 982-983
Author(s):  
R.J. Mount ◽  
R.V. Harrison
Keyword(s):  
Basilar Membrane ◽  
Low Cost ◽  
Organ Of Corti ◽  
Region Of Interest ◽  
Sensory Epithelium ◽  
Physical Damage ◽  
Air Drying ◽  
Specimen Handling ◽  
Two Component

The sensory end organ of the ear, the organ of Corti, rests on a thin basilar membrane which lies between the bone of the central modiolus and the bony wall of the cochlea. In vivo, the organ of Corti is protected by the bony wall which totally surrounds it. In order to examine the sensory epithelium by scanning electron microscopy it is necessary to dissect away the protective bone and expose the region of interest (Fig. 1). This leaves the fragile organ of Corti susceptible to physical damage during subsequent handling. In our laboratory cochlear specimens, after dissection, are routinely prepared by the O-T- O-T-O technique, critical point dried and then lightly sputter coated with gold. This processing involves considerable specimen handling including several hours on a rotator during which the organ of Corti is at risk of being physically damaged. The following procedure uses low cost, readily available materials to hold the specimen during processing ,preventing physical damage while allowing an unhindered exchange of fluids.Following fixation, the cochlea is dehydrated to 70% ethanol then dissected under ethanol to prevent air drying. The holder is prepared by punching a hole in the flexible snap cap of a Wheaton vial with a paper hole punch. A small amount of two component epoxy putty is well mixed then pushed through the hole in the cap. The putty on the inner cap is formed into a “cup” to hold the specimen (Fig. 2), the putty on the outside is smoothed into a “button” to give good attachment even when the cap is flexed during handling (Fig. 3). The cap is submerged in the 70% ethanol, the bone at the base of the cochlea is seated into the cup and the sides of the cup squeezed with forceps to grip it (Fig.4). Several types of epoxy putty have been tried, most are either soluble in ethanol to some degree or do not set in ethanol. The only putty we find successful is “DUROtm MASTERMENDtm Epoxy Extra Strength Ribbon” (Loctite Corp., Cleveland, Ohio), this is a blue and yellow ribbon which is kneaded to form a green putty, it is available at many hardware stores.

Sign in / Sign up

Export Citation Format

Share Document