Joint Photographic Experts Group Algorithm Research Articles

Reduction of computation time in differential evolution-based quantisation table optimisation for the JPEG baseline algorithm

The design of quantisation table is viewed as an optimisation problem because the quantisation table produces the compression/quality trade-off in baseline joint photographic experts group algorithm. In this paper, efforts have been taken to reduce the computation time of the differential evolution (DE) algorithm by using the surrogate model. This paper applies a problem approximation surrogate model (PASM) to assist DE algorithms for optimising the quantisation table. It also analyses the performance of PASM in DE algorithm based on approximation error and evolutionary perspective. In addition, it confirms the results using statistical hypothesis tests. PASM is integrated in classical differential evolution and knowledge-based differential evolution algorithms. Different benchmark images are used to validate the PASM performance in DE algorithms for three target bits per pixel. The result shows that integrated PASM in DE algorithms reduces the computation time and guarantees the similar results as DE algorithms without a model.

SU‐E‐I‐16: A Data Compression Device for 4D CBCT

Purpose: 4D Cone beam computed tomography (CBCT) produce hundreds of images daily which are useless for diagnosis. A key problem is to effectively compress these similar imaging data daily and easily invoke them when necessary. The aim of this study is to develop a data compression device for CBCT with appropriate compressing ratio and reserving the image quality. Methods: Kilovoltage (kV) CBCT image from one patient was acquired for each treatment fraction to correct patient setup. The transverse CBCT images were reconstructed from the raw data using a XVI system. The compression device was written in C++ using dicomtk library, allowing a selectable tradeoff between storage size and image quality, then Qt software which is a cross‐platform application and UI framework was used to package this compression algorithm. In this study, JPEG (Joint Photographic Experts Group) algorithm was employed since it is the most commonly method for imaging processing. Results: After compression, the original 1.53GB file was compressed to 461.1MB for lossless while 264.3MB for lossy compression. To evaluate the impact of the lossy compression on image quality, the compressed image and the original image were compared by using PSNR (Peak signal noise ratio), there were no obvious distortions between them. Conclusion: A new effective data compression device for CBCT is developed without apparent influence on the image quality, and this could improve the efficiency of daily 4D CBCT and fascinate other advanced treatment techniques like adaptive tumor detection and tracking.

Filter Augmented JPEG Algorithms: A Critical Performance Study for Improving Bandwidth

recent years, use of Digital Image Communication has increased exponentially in the day to day activities. Joint Photographic Experts Group (JPEG) is the most widely used still image compression standard for bandwidth conservation. In this paper, it is proposed and critically studied a new set of JPEG Compression algorithms by combining Mean filtering, Median filtering, and Outlier detection algorithms and conventional JPEG DCT algorithm in a staged manner. This outlier based JPEG algorithm is giving exceptionally compression compared to conventional JPEG algorithm. Experiments are carried out with many standard still images. Algorithms developed in this paper, identified to be giving almost same Peak Signal-to-Noise Ratio (PSNR) as that of standard JPEG algorithm.

Hardware Software Co-Design for JPEG Encoder Test Bench

This paper presents a hardware/software (HW/SW) co-design approach using System On a Programmable Chip (SOPC) technique to achieve Joint Photographic Experts Group (JPEG) algorithm. It firstly introduces JPEG image compression technology and the system architecture. Then the hardware/software design process of JPEG encoder test bench is introduced. It focuses on using the characteristics of Field-Programmable Gate Array (FPGA) structure to achieve JPEG algorithm including the improved Discrete Cosine Transform (DCT), and Nios II embedded processor of customizable characteristics, translating image acquisition, JPEG image compression and Thin Film Transistor Liquid Crystal Display (TFT-LCD) controller into user-defined modules according to Altera Avalon bus requirements with the SOPC Builder, where the user-defined module can be added to the system under the control of soft-core Nios II Embedded. Finally, the whole system is verified on a single FPGA chip. The experimental results shows the advantages of JPEG algorithm as a FPGA hardware module includes low power consumption, high image quality, low production costs and stable performance. There’s a very great practical significance to reduce costs and improve image processing speed.

Evaluation of the effect of JPEG and JPEG2000 image compression on the detection of diabetic retinopathy

To compare the effect of classic Joint Photographic Experts Group (JPEG) and JPEG2000 compression algorithms on detection of diabetic retinopathy (DR) lesions. In total, 45 colour fundus photographs obtained with a digital nonmydriatic fundus camera were saved in uncompressed Tagged Interchanged Files Format (TIFF) format (1.26 MB). They were graded jointly by two retinal specialists at a 1 month interval for soft exudates, hard exudates, macular oedema, newvessels, intraretinal microvascular abnormalities (IRMA), and retinal haemorrhages and/or microaneurysms. They were compressed to 118, 58, 41, and 27 KB by both algorithms and 24 KB by classic JPEG, placed in random order and graded again jointly by the two retina specialists. Subjective image quality was graded, and sensitivity, specificity, positive and negative predictive values, and kappa statistic were calculated for all lesions at all compression ratios. Compression to 118 KB showed no effect on image quality and kappa values were high (0.94-1). Image degradation became important at 27 KB for both algorithms. At high compression levels, IRMA and HMA detection were most affected with JPEG2000 performing slightly better than classic JPEG. Performance of classic JPEG and JPEG2000 algorithms is equivalent when compressing digital images of DR lesions from 1.26 MB to 118 KB and 58 KB. Higher compression ratios show slightly better results with JPEG2000 compression, but may be insufficient for screening purposes.

Acute cerebral infarction: effect of JPEG compression on detection at CT.

To evaluate the effect of Joint Photographic Experts Group (JPEG) compression ratios of 10:1 and 20:1 on detection of acute cerebral infarction at computed tomography (CT). CT images obtained in 25 patients with acute cerebral infarction and 25 patients with no lesions were compressed by means of a JPEG algorithm at ratios of 10:1 and 20:1. Normal and abnormal sections (on original and compressed images) were reviewed by using a color soft-copy computed monochrome cathode ray tube monitor. Five observers rated the presence or absence of a lesion with a 50-point scale (0, definitely absent; 25, equivocal; and 50, definitely present). Diagnostic accuracy was evaluated with receiver operating characteristic (ROC) curve analysis. Significant difference was defined as a P value less than.05 for the area tested with a two-tailed paired Student t test. At ROC analysis, no statistically significant difference was detected for all cases considered together (Az [area under the ROC curve] = 0.887 +/- 0.038 [mean +/- SD] on noncompressed images, Az = 0.897 +/- 0.038 on 10:1 compressed images, and Az = 0.842 +/- 0.073 on 20:1 compressed images; P >.05). JPEG compression at ratios of 10:1 and 20:1 was tolerated in the detection of acute cerebral infarction at CT.

EFFECTS OF JPEG AND WAVELET COMPRESSION OF SPIRAL LOW-DOSE CT IMAGES ON DETECTION OF SMALL LUNG CANCERS

To compare the effect of compression of spiral low-dose CT images by the Joint Photographic Experts Group (JPEG) and wavelet algorithms on detection of small lung cancers. Low-dose spiral CT images of 104 individuals (52 with peripheral lung cancers smaller than 20 mm and 52 control subjects) were used. The original images were compressed using JPEG or wavelet algorithms at a ratio of 10:1 or 20:1. Five radiologists interpreted these images and evaluated the image quality on a high-resolution CRT monitor. Observer performance was studied by receiver operating characteristic (ROC) analysis. There was no significant difference in the detection of cancers measuring 6 to 15 mm in uncompressed images and in those compressed by either of the algorithms, although the quality of images compressed at 20:1 with the wavelet algorithm was somewhat inferior. A lower diagnostic accuracy was noted using images compressed by the JPEG or wavelet algorithms at 20:1 in detecting lung cancers measuring 6 to 10 mm and cancers measuring from 6 to 15 mm with ground-glass opacity. Compression of low-dose CT images at a ratio of 10:1 using JPEG and wavelet algorithms does not compromise the detection rate of small lung cancers.

Effect of CT digital image compression on detection of coronary artery calcification.

To test the effect of digital compression of CT images on the detection of small linear or spotted high attenuation lesions such as coronary artery calcification (CAC). Fifty cases with and 50 without CAC were randomly selected from a population that had undergone spiral CT of the thorax for screening lung cancer. CT image data were compressed using JPEG (Joint Photographic Experts Group) or wavelet algorithms at ratios of 10:1, 20:1 or 40:1. Five radiologists reviewed the uncompressed and compressed images on a cathode-ray-tube. Observer performance was evaluated with receiver operating characteristic analysis. CT images compressed at a ratio as high as 20:1 were acceptable for primary diagnosis of CAC. There was no significant difference in the detection accuracy for CAC between JPEG and wavelet algorithms at the compression ratios up to 20:1. CT images were more vulnerable to image blurring on the wavelet compression at relatively lower ratios, and "blocking" artifacts occurred on the JPEG compression at relatively higher ratios. JPEG and wavelet algorithms allow compression of CT images without compromising their diagnostic value at ratios up to 20:1 in detecting small linear or spotted high attenuation lesions such as CAC, and there was no difference between the two algorithms in diagnostic accuracy.

EFFECT OF CT DIGITAL IMAGE COMPRESSION ON DETECTION OF CORONARY ARTERY CALCIFICATION

To test the effect of digital compression of CT images on the detection of small linear or spotted high attenuation lesions such as coronary artery calcification (CAC). Fifty cases with and 50 without CAC were randomly selected from a population that had undergone spiral CT of the thorax for screening lung cancer. CT image data were compressed using JPEG (Joint Photographic Experts Group) or wavelet algorithms at ratios of 10:1, 20:1 or 40:1. Five radiologists reviewed the uncompressed and compressed images on a cathode-ray-tube. Observer performance was evaluated with receiver operating characteristic analysis. CT images compressed at a ratio as high as 20:1 were acceptable for primary diagnosis of CAC. There was no significant difference in the detection accuracy for CAC between JPEG and wavelet algorithms at the compression ratios up to 20:1. CT images were more vulnerable to image blurring on the wavelet compression at relatively lower ratios, and "blocking" artifacts occurred on the JPEG compression at relatively higher ratios. JPEG and wavelet algorithms allow compression of CT images without compromising their diagnostic value at ratios up to 20:1 in detecting small linear or spotted high attenuation lesions such as CAC, and there was no difference between the two algorithms in diagnostic accuracy.

Restoration of Image Deteriorated by JPEG Compression

JPEG (Joint Photographic Experts Group) algorithm is widely used in imaging system. When image data are highly compressed by JPEG, the image is deteriorated. Deterioration of false contour and mosquito noise is mainly felt. In the restoration, false contour area is extracted and is smoothed by fitting method of least squares algorithm. Improved result is obtained, compared with the former method proposed by us.

An analytical look at the effects of compression on medical images.

This article will take an analytical look at how lossy Joint Photographic Experts Group (JPEG) and wavelet image compression techniques affect medical image content. It begins with a brief explanation of how the JPEG and wavelet algorithms work, and describes in general terms what effect they can have on image quality (removal of noise, blurring, and artifacts). It then focuses more specifically on medical image diagnostic content and explains why subtle pathologies, that may be difficult for the human eye to discern because of low contrast, are generally very well preserved by these compression algorithms. By applying a wavelet decomposition to the whole image and to specific regions of interest (ROI), and by understanding how the lossy quantization step attenuates signals in those decomposition energy subbands, much can be learned about how tolerant various anatomical structures are to compression. High-frequency anatomical structures that have their energy represented by a few large coefficients (in the wavelet domain) will be well preserved, while, those structures with high frequency energy distributed over numerous smaller coefficients are the most vulnerable to compression. Digitized films showing subtle chest nodules, a subtle stress fracture, and CT and MR images are used to show these results.

A Fast 8 × 8 Pruned DCT Algorithm

El-Sharkawy, M., and Eshmawy, W., A Fast 8 × 8 Pruned DCT Algorithm,Digital Signal Processing6 (1996), 145–154.A new algorithm that computes the 8 × 8 pruned Discrete Cosine Transform (DCT) using the vector–radix approach is introduced. The vector–radix approach decomposes the 8 × 8 pruned DCT into four 4 × 4 pruned DCTs. The 4 × 4 pruned DCT is then decomposed into four one-dimensional pruned DCTs. The number of points that need to be calculated from each one-dimensional DCT depends on the allowed amount of pruning. The proposed algorithm does not require any bit reversal operations. To illustrate the usefulness of the proposed pruned DCT algorithm, we utilize it to compress images using a Joint Photographic Experts Group (JPEG) algorithm. The proposed 8 × 8 pruned DCT algorithm improves the compression ratio and reduces both the complexity and execution time of the modified JPEG algorithm.

Experimental evaluation of psychophysical distortion metrics for JPEG-encoded images

Two experiments for evaluating psychophysical distortion metrics in Joint Photographic Experts Group (JPEG) encoded images are described. The first is a threshold experiment, in which subjects determined the bit rate or level of distortion at which distortion was just noticeable. The second is a suprathreshold experiment in which subjects ranked image blocks according to perceived distortion. The results of these experiments were used to determine the predictive value of a number of computed image distortion metrics. It was found that mean-square-error is not a good predictor of distortion thresholds or suprathreshold perceived distortion. Some simple pointwise measures were in good agreement with psychophysical data; other more computationally intensive metrics involving spatial properties of the human visual system gave mixed results. It was determined that mean intensity, which is not accounted for in the JPEG algorithm, plays a significant role in perceived distortion.