Joint Photographic Experts Group Images Research Articles

JPEG Image Transmission over Rayleigh Fading Channel with Unequal Error Protection

In this paper an image transmission system has been proposed where Joint Photographic Experts Group (JPEG) algorithm is used as an image coder and Rate Compatible Punctured Convolution (RCPC) channel coder is used for transmission of coded image over wireless channels (AWGN and Rayleigh fading). JPEG bit stream is partitioned into DC and AC bit streams. AC bit stream further classified using edge density property of block. Priorities based Unequal error Protection (UEP) applied to bit stream. Distortion analysis (MSE) is given for proposed image transmission scheme. The simulation results shows reduction in distortion compared to conventional Equal Error Protection (EEP). This proposed algorithm can be applied for low frequency as well as high frequency images. General Terms Image Coding and transmission through wireless channel

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.

The effects of image compression on quantitative measurements of digital panoramic radiographs

Objectives: The aims of this study were to explore how image compression affects density, fractal dimension, linear and angular measurements on digital panoramic images and assess inter and intra-observer repeatability of these measurements. Study Design: Sixty-one digital panoramic images in TIFF format (Tagged Image File Format) were compressed to JPEG (Joint Photographic Experts Group) images. Two observers measured gonial angle, antegonial angle, mandibular cortical width, coronal pulp width of maxillary and mandibular first molar, tooth length of maxillary and mandibular first molar on the left side of these images twice. Fractal dimension of the selected regions of interests were calculated and the density of each panoramic radiograph as a whole were also measured on TIFF and JPEG compressed images. Intra-observer and inter-observer consistency was evaluated with Cronbach’s alpha. Paired samples t-test and Kolmogorov-Smirnov test was used to evaluate the difference between the measurements of TIFF and JPEG compressed images. Results: The repeatability of angular measurements had the highest Cronbach’s alpha value (0.997). There was statistically significant difference for both of the observers in mandibular cortical width (MCW) measurements (1st ob. p: 0.002; 2nd ob. p: 0.003), density (p<0.001) and fractal dimension (p<0.001) between TIFF and JPEG images. There was statistically significant difference for the first observer in antegonial angle (1st ob p< 0.001) and maxillary molar coronal pulp width (1st ob. p<0.001) between JPEG and TIFF files. Conclusions: The repeatability of angular measurements is better than linear measurements. Mandibular cortical width, fractal dimension and density are affected from compression. Observer dependent factors might also cause statistically significant differences between the measurements in TIFF and JPEG images. Key words:Digital panoramic radiography, image compression, linear measurements, angular measurements, fractal dimension.

Image Compression Impact on Quantitative Angiogenesis Analysis of Ovarian Epithelial Neoplasms

This study aims to investigate the impact of digital image compression on manual and semiautomatic quantification of angiogenesis in ovarian epithelial neoplasms (including benign, borderline, and malignant specimens). We examined 405 digital images (obtained from a previously validated computer-assisted analysis system), which were equally divided into 5 groups: images captured in Tagged Image File Format (TIFF), low and high compression Joint Photographic Experts Group (JPEG) formats, and low and high compression JPEG images converted from the TIFF files. Microvessel density counts and CD34 endothelial areas manually and semiautomatically determined from TIFF images were compared with those from the other 4 groups. Mostly, the correlations between TIFF and JPEG images were very high (intraclass correlation coefficients >0.8), especially for low compression JPEG images obtained by capture, regardless of the variable considered. The only exception consisted in the use of high compression JPEG files for semiautomatic microvessel density counts, which resulted in intraclass correlation coefficients of <0.7. Nonetheless, even then, interconversion between TIFF and JPEG values could be successfully achieved using prediction models established by linear regression. Image compression does not seem to significantly compromise the accuracy of angiogenesis quantitation in the ovarian epithelial tumors, although low compression JPEG images should always be preferred over high compression ones.

Improved contourlet-based steganalysis using binary particle swarm optimization and radial basis neural networks

Steganography is the science of hiding information in a media such as video, image or audio files. On the other hand, the aim of steganalysis is to detect the presence of embedded data in a given media. In this paper, a steganalysis method is presented for the colored joint photographic experts group images in which the statistical moments of contourlet transform coefficients are used as the features. In this way, binary particle swarm optimization algorithm is also employed as a closed-loop feature selection method to select the efficient features in tandem with improvement of the detection rate. Nonlinear support vector machine and two variants of radial basis neural networks, i.e., radial basis function and probabilistic neural network, are used as the classification tools and their performance is compared in detecting the stego and clean images. Experimental results show that even for low embedding rates, the detection accuracy of the proposed method is more than 80% along with 30% reduction in the size of feature set.

Comparison and Analysis of Discrete Cosine Transform based Joint Photographic Experts Group Image Compression using Robust Watermarking Algorithm

Problem statement: The performance of the watermarking algorithms is analyzed using different compression standards to study the watermark extraction behavior of these algorithms. Approach: A digital watermarking method is said to be effective if the watermark embedded in an image by it could survive against diverse attacks ranging from compression, filtering to cropping. Several techniques are presented in the literature for robust watermarking algorithm to defend against the various the compression methods. Results: In this study, we have presented comparison and analysis of recently developed watermarking algorithms. Then, an extensive analysis is carried out to estimate and compare robustness of watermarking algorithms by considering the visual quality of the original and watermarked images in terms of Peak Signal to Noise Ratio. Furthermore, the extracting fidelity of the watermarking algorithms is compared by taking the Normalized Correlation value between the original watermark and the extracted watermark. Conclusion/Recommendations: The experimental results showed the accuracy of different watermarking algorithms in terms of visual quality and fidelity.

Establishment Threshold Value of Image Realization & Reconstruction of Stoppage Image using Picture Resemblance

In this paper, JPEG(Joint Photographic Experts Group) image data video decoding technique is presented, it is Huffman decoding method and fractal image method which is very complexive algorithm and the time required much it to implement this method and the first image is decoded to video frame image. This have defect of overlap decoding and transport work because of impossible to represent objective value of resemblance. The proposed method was calculated the mathematical absolute image resemblance and simplify the moving picture process to reducing the step of moving picture codefying. The results show that smoothed moving picture compared recent methods.

Detecting Double JPEG Compression With the Same Quantization Matrix

Detection of double joint photographic experts group (JPEG) compression is of great significance in the field of digital forensics. Some successful approaches have been presented for detecting double JPEG compression when the primary compression and the secondary compression have different quantization matrixes. However, when the primary compression and the secondary compression have the same quantization matrix, no detection method has been reported yet. In this paper, we present a method which can detect double JPEG compression with the same quantization matrix. Our algorithm is based on the observation that in the process of recompressing a JPEG image with the same quantization matrix over and over again, the number of different JPEG coefficients, i.e., the quantized discrete cosine transform coefficients between the sequential two versions will monotonically decrease in general. For example, the number of different JPEG coefficients between the singly and doubly compressed images is generally larger than the number of different JPEG coefficients between the corresponding doubly and triply compressed images. Via a novel random perturbation strategy implemented on the JPEG coefficients of the recompressed test image, we can find a “proper” randomly perturbed ratio. For different images, this universal “proper” ratio will generate a dynamically changed threshold, which can be utilized to discriminate the singly compressed image and doubly compressed image. Furthermore, our method has the potential to detect triple JPEG compression, four times JPEG compression, etc.

Ｃｏｍｐｕｔｅｄ Ｒａｄｉｏｇｒａｐｈｙにおける非可逆圧縮画像の物理特性

Joint photographic experts group(JPEG)and JPEG2000 are widely used as image compression algorithms in medical image database systems. Compressed images have been mainly evaluated by visual assessment on acceptable compression levels in clinical studies. However, to the best of our knowledge, little work has been done to clarify image properties based on physical analysis. In this work, investigations were made to clarify image properties based on physical analysis and to discuss the major causes of degradation related to compression ratios. The physical properties of JPEG2000-compressed and JPEG-compressed images in computed radiography(CR)were compared by measuring the characteristic curve, modulation transfer function(MTF), noise power spectrum(NPS), peak signal-to-noise ratio(PSNR), contrast-to-noise ratio(CNR), and noise equivalent quanta(NEQ). In the MTF measurement, the MTFs of JPEG at high compression ratio showed pronounced degradation at all frequencies. The NPS values of JPEG2000 tend to decrease considerably compared to that of the JPEG at all frequencies with the increase of compression ratio. Furthermore, JPEG2000 images showed higher PSNR, CNR, and NEQ values than JPEG images in the same compression ratio. In these signal-to-noise ratio measurements, good reproducibility of JPEG2000 images was achieved. Overall, JPEG2000 compressed images were far superior to JPEG compressed images. In the physical properties measured, these physical analyses are useful to comprehend physical properties for each irreversible compressed image related to compression ratios in CR.

The Effect of Wavelet and Discrete Cosine Transform Compression of Digital Radiographs on the Detection of Subtle Proximal Caries

The study compared diagnostic performances of 2 different image compression methods: JPEG (discrete cosine transform; Joint Photographic Experts Group compression standard) versus JPEG2000 (discrete wavelet transform), both at a compression ratio of 12:1, from the original uncompressed TIFF radiograph with respect to the detection of non-cavitated carious lesions. Therefore, 100 approximal surfaces of 50 tooth pairs were evaluated on the radiographs by 10 experienced observers using a 5-point confidence scale. Observations were carried out on a standardized viewing monitor under subdued light conditions. The proportion of diseased surfaces was balanced to approximately 50% to avoid bias. True caries status was assessed by serial ground sectioning and microscopic evaluation. A non-parametric receiver operating characteristic analysis revealed non-significant differences between the 3 image modalities, as computed from the critical ratios z not exceeding ±2 (JPEG/JPEG2000, z = –0.0339; TIFF/JPEG2000, z = 0.251;TIFF/JPEG, z = 0.914). The mean area beneath the curve was highest for TIFF (0.604) followed by JPEG2000 (0.593) and JPEG (0.591). Both intra-rater and inter-rater agreement were significantly higher for TIFF (ĸ_intra = 0.52; ĸ_inter = 0.40) and JPEG2000 images (ĸ_intra = 0.49; ĸ_inter = 0.38) than for JPEG images (ĸ_intra = 0.33; ĸ_inter = 0.35). Our results indicate that image compression with typical compression algorithms at rates yielding storage sizes of around 50 kB is sufficient even for the challenging task of radiographic detection of non-cavitated carious approximal lesions.

Transmission of modified JPEG images through AWGN channel

Joint Photographic Experts Group (JPEG) is a standard for compressing continuous-tone images. In this paper, image is compressed based on JPEG, but in place of Huffman coding, Run Length Encoding (RLE)/Vector Quantisation (VQ) has been applied and performance evaluated. RLE does not require table storage, but produces lesser compression than Huffman. VQ achieves higher compression at the cost of reduced quality. Further, the reconstructed image has been filtered to reduce blocking artifacts. When the encoded image is corrupted with Additive White Gaussian Noise (AWGN), VQ is more robust than Huffman/RLE since it is fixed-length encoding technique.

Web-Based Grading of Compressed Stereoscopic Digital Photography versus Standard Slide Film Photography for the Diagnosis of Diabetic Retinopathy

To evaluate the ability of Joint Photographic Experts Group (JPEG) compressed, stereoscopic, digital photography to identify clinical levels of diabetic retinopathy, detect clinically significant macular edema (CSME), and make appropriate referral recommendations as compared with Early Treatment Diabetic Retinopathy Study (ETDRS) standard film photography. Prospective, clinic-based, comparative photographic format validation study. Two hundred four eyes from 102 consecutive, new, diabetic patients with a median duration of diabetes of 12.5 years were enrolled and analyzed. After pupillary dilation, a trained ophthalmic photographer obtained 2 sets of images: standard ETDRS, stereoscopic 7-field 35-mm film photographs and high-resolution, digital images of the same 7 standard fields (stereoscopic images of fields 1 and 2). Two masked readers graded both sets of images. The 35-mm film photographs were graded by hand using a written template. Digital photographs were compressed, uploaded to a web site, and graded by a web-based, computer-assisted ETDRS algorithm. The ETDRS level of diabetic retinopathy, presence of retinal thickening, and referral recommendation based on these 2 diagnoses were recorded and compared. The presence of CSME, ETDRS level of diabetic retinopathy, and referral threshold diabetic retinopathy. Film and compressed digital grading levels were compared using a simplified ETDRS categorization scheme. Film and digital gradings were highly correlated with exact agreements for level of diabetic retinopathy, CSME, and referral thresholds >87% and kappa levels >0.71. McNemar's testing found no statistically significant difference between compressed digital images and film when comparing referral thresholds (defined as the presence of CSME and/or ETDRS level > or = 61; P = 0.76). A modified ETDRS protocol (stereoscopic images of fields 1 and 2 only) with 16:1 JPEG image compression and computer-assisted ETDRS grading algorithm has excellent reproducibility when compared to standard ETDRS stereoscopic slide-film photography. An internet-based teleophthalmology system can correctly and reliably (kappa = 0.78) identify patients requiring referral for CSME and proliferative diabetic retinopathy (PDR; ETDRS level > or = 61).

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.

An error resilient coding scheme for JPEG image transmission based on data embedding and side-match vector quantization

For an entropy-coded Joint Photographic Experts Group (JPEG) image, a transmission error in a codeword will not only affect the underlying codeword but also may affect subsequent codewords, resulting in a great degradation of the received image. In this study, an error resilient coding scheme for JPEG image transmission based on data embedding and side-match vector quantization (VQ) is proposed. To cope with the synchronization problem, the restart capability of JPEG images is enabled. The objective of the proposed scheme is to recover high-quality JPEG images from the corresponding corrupted images. At the encoder, the important data (the codebook index) for each Y (U or V) block in a JPEG image are extracted and embedded into another “masking” Y (U or V) block in the image by the odd–even data embedding scheme. At the decoder, after all the corrupted blocks within a JPEG image are detected and located, if the codebook index for a corrupted block can be correctly extracted from the corresponding “masking” block, the extracted codebook index will be used to conceal the corrupted block; otherwise, the side-match VQ technique is employed to conceal the corrupted block. Based on the simulation results obtained in this study, the performance of the proposed scheme is better than those of the five existing approaches for comparison. The proposed scheme can recover high-quality JPEG images from the corresponding corrupted images up to a block loss rate ( BLR) of 30%.

JPEG compression of stereoscopic digital images for the diagnosis of diabetic retinopathy via teleophthalmology

Background: Canada's vast size and remote rural communities represent a significant hurdle for successful monitoring and evaluation of diabetic retinopathy.Teleophthalmology may provide a solution to overcome this problem. We investigated the application of joint Photographic Experts Group (JPEG) compression to digital retinal images to determine whether JPEG compression could reduce file sizes while maintaining sufficient quality and detail to accurately diagnose diabetic retinopathy.Methods: All 20 patients with type 2 diabetes mellitus assessed at a 1-day teleophthalmology clinic in northern Alberta were enrolled in the study. Following pupil dilation, seven 30° fields of each fundus were digitally photographed at a resolution of 2008 × 3040 pixels and saved in uncompressed tagged image file format (TIFF). The files were compressed approximately 55× and 113× their original size using JPEG compression. A reviewer in Edmonton randomly viewed all original TIFF images along with the compressed JPEG images in a masked fashion for image quality and for specific diabetic retinal pathology in accordance with Early Treatment Diabetic Retinopathy Study standards. The level of diabetic retinopathy and recommendations for clinical follow-up were also recorded. Exact agreement and weighted κ statistics, a measure of reproducibility, were calculated.Results: Exact agreement between the compressed JPEG images and the TIFF images was high (75% to 100%) for all measured variables at both compression levels. Reproducibility was good to excellent at both compression levels for the identification of diabetic retinal abnormalities (κ = 0.45–1), diagnosis of level of retinopathy (κ = 0.73–1) and recommended follow-up (κ = 0.64–1).Interpretation: The application of JPEG compression at ratios of 55:1 and 113:1 did not significantly interfere with the identification of specific diabetic retinal pathology, diagnosis of level of retinopathy or recommended follow-up.These results indicate that JPEG compression at ratios as high as 113:1 has the potential to reduce storage requirements without interfering with the accurate and reproducible teleophthalmologic diagnosis of diabetic retinopathy. This pilot project demonstrates the potential for JPEG compression within a digital teleophthalmology viewing system.

Retrieving digital images from a JPEG compressed image database

In this paper, we propose a new method of feature extraction in order to improve the efficiency of retrieving Joint Photographic Experts Group (JPEG) compressed images. Our feature extraction can be done directly to JPEG compressed images. We extract two features, DC feature and AC feature, from a JPEG compressed image. Then we measure the distances between the query image and the images in a database in terms of these two features. Our image retrieval system will give each retrieved image a rank to define its similarity to the query image. Furthermore, instead of fully decompressing JPEG images, our system only needs to do partial entropy decoding. Therefore, our proposed scheme can accelerate the work of retrieving images. According to our experimental results, our system is not only highly efficient but is also capable of performing satisfactorily.

Radiology Image Management in a Teaching Hospital Network Scenario: Initial Experience.

INHS Asvini has the distinction of emerging as the first Armed Forces Hospital with networked radiology images, sourced principally from a recently installed Digital Substraction Angiography (DSA) machine (Siemens Polystar Top 1000 MA). In recent times, newer imaging machines offer digital images that are in DICOM format. DICOM denotes 'Digital Imaging and Communications in Medicine". Image management at INHS Asvini, involves transfer of DSA images in DICOM format, their conversion into Joint Photographic Experts Group (JPG) format and subsequent transmission of JPG images through a robust networking system that connects all departments/OPD/Wards, facilitating direct access of images to a variety of specialists and specialities. Clearly, this encouraging outcome is a small but useful step heralding the concept of 'anytime anywhere' images, and has the scalable expansibility of including CT and MRI images in future.

Transmission of JPEG-coded images over wireless channels

The Joint Photographic Experts Group (JPEG) standard is widely used for coding still images. It is very sensitive to transmission errors and can be employed successfully only when the transmission channel is nearly error free. Wireless communication channels are characterized by long bursts of data errors, and average bit error rates (BERs) of 10−3 to 10−4 are typical in cellular mobile radio channels. This paper presents an efficient scheme to transmit JPEG-coded images over wireless channels. In addition, some postprocessing techniques — used for error concealment of JPEG images transmitted over wireless channels — are discussed. The paper also demonstrates the effectiveness of the postprocessing techniques for a diverse set of images obtained from indoor radio channel experiments.

The effects of different image file formats and image-analysis software programs on dental radiometric digital evaluations.

To determine if variations in radiodensity data are introduced by lossy Joint Photographic Experts Group (JPEG) compression and/or the use of three software programs. An occlusal film with an aluminium step wedge was exposed, processed and digitized under standard conditions. Before the image was saved, the coordinates and the gray-scale value for each pixel in a 20 x 20 pixel area near the middle of the thickest step were recorded. These pixel coordinates and gray-scale values served as Truth 1. In addition, a digital simulated-radiographic image with assigned gray-scale values for each pixel was created and served as Truth 2. The digital data for the scanned radiograph and the simulated radiograph were saved as Tagged Image File Format (TIFF) and lossy JPEG files. Each file was opened with three software programs and the gray-scale values of homologous pixels were recorded. For these pixels in each image type, the mean gray-scale values and standard deviations were calculated. The pixel gray-scale values for each homologous pixel were also individually compared. When the TIFF images were opened with the three software programs, one program resulted in gray-scale values that were not concordant with truth. All JPEG images resulted in gray-scale values that were not concordant with truth. One software program added a column of 0s to data files. Lossy JPEG compression introduced potentially deleterious variations to radiodensity data, and at least two of the software programs performed JPEG image decompression differently.

GRADING, IMAGE ANALYSIS, AND STEREOPSIS OF DIGITALLY COMPRESSED FUNDUS IMAGES

To investigate the effects of image digitization and compression on the ability to identify and quantify features in color fundus photographs. Color fundus photographs were digitized as tagged image file format (TIFF) and high-compression (80:1) and low-compression (30:1) joint photographic experts group (JPEG) images. Rerendered images were subjected to standard grading protocols developed for a clinical trial, and digitized images were subjected to image analysis software for drusen identification and quantitation. Re-created stereoscopic images were compared subjectively with originals. Original, TIFF, and low-compression (30:1) JPEG images were virtually indistinguishable when subjected to close scrutiny with magnification. The overall quality of high-compression (80:1) JPEG images and images digitized at 500 dots per inch was markedly reduced. Protocol grading of original and digitized images was highly concordant within the repeatability of multiple grading of original images. The area subtended by drusen differed by less than 1.0% for all uncompressed and compressed image pairs quantified. Stereoscopic information was accurately preserved when compared with originals for TIFF and low-compression JPEG images. Fundus images can be digitized and stored with significant compression while preserving stereopsis and image quality suitable for quantitative image analysis and semiquantitative grading. Low-compression (30:1) JPEG images may be suitable for archiving and telemedical applications.