High‐quality image magnification applying the gerchberg‐papoulis iterative algorithm with DCT

To study the effect of decentration and tilt of the type I Boston keratoprosthesis (KPro) on image quality in both aphakic and pseudophakic eyes. An optical ray-tracing program was used to simulate the image projected onto the retina in an eye with a perfectly centered KPro, and in eyes with varying degrees of KPro decentration and tilt. Decentration was modeled along a typical white-to-white distance of 12.0 mm, and the corresponding tilt was calculated assuming a radius of curvature of 8.0 mm, the radius of curvature of the backplate of the KPro. Both aphakic and pseudophakic eyes were simulated, and the corresponding modulation transfer function curves, point spread functions, and astigmatism were analyzed. The perfectly centered KPro produced a high-quality image with no induced astigmatism. Increasing decentration beyond approximately 0.5 mm resulted in poorer image quality with a more pronounced effect in the presence of an intraocular lens. Using models of the normal eye as a threshold, image degradation due to decentration becomes clinically significant at approximately 1.4 mm and 0.9 mm for the aphakic and pseudophakic cases, respectively. Astigmatism introduced by decentration is approximately 0.25 D cylinders at those thresholds. Decentration of up to 0.5 mm had no significant impact on image quality and an attempt at good intraoperative centration of the KPro within this range is important. Conversely, decentration of 0.9 mm or more during surgical implantation can result in significant degradation in retinal image quality including astigmatism. The effect is greater in the pseudophakic eye.

Area-based matching is a fundamental image processing operation to obtain the displacement between images. Also, the similarity interpolation method to estimate subpixel displacement is commonly used to enhance resolution. Conventionally, similarity interpolation estimation is performed by assuming that the horizontal and vertical displacements are independent. Almost no investigations of estimation error over the conventional method have been made, but it is inferred experientially that subpixel estimation with image interpolation or gradient-based methods is more precise than the similarity interpolation method. This paper proposes a novel 2D subpixel displacement estimation method based on similarity interpolation through modeling of 2D self-similarity. The proposed method requires no “a priori” knowledge of 2D similarity and no images at all. It adopts no iteration. Furthermore, the proposed method entails only slightly higher calculation costs than the conventional similarity interpolation method. The proposed method can obtain more precise estimation than both the conventional similarity interpolation method and the image interpolation method using comparison of subpixel estimation accuracy. An experiment using actual images demonstrates the effectiveness of the proposed method. © 2005 Wiley Periodicals, Inc. Syst Comp Jpn, 36(2): 1–11, 2005; Published online in Wiley InterScience (). DOI 10.1002sscj.20221

Image interpolation, with its image magnifying abilities, is an image processing operation of increasing importance in the fields of biology and medicine. In this paper, we present a novel image interpolation technique that utilizes the discrete cosine transform (DCT). The DCT provides for a decrease in border effects, and improves the processing speed. The advantages of this technique over the traditional Fourier-transform-based techniques stem from basic properties of DCT that it is a non-periodic, real (non-complex) transform with excellent energy compaction in the transform domain. In fact, the DCT's energy compaction property is next only to Karhunen-Loeve transform in the mean squared sense on an ensemble of images (Jain, 1989). In addition, DCT allows interpolation of small volumes (e.g., 8/spl times/8/spl times/8) which is not easily possible with an FFT-based method. Therefore, the present technique is better suited for applications such as a real-time 3D interactive maximum intensity projection, real-time 2-D image magnifier etc. More importantly, the technique can be used for the bandlimited interpolation of any digitally acquired data to minimize partial voluming artifact.

In computer vision and image processing, image interpolation has been used widely to perform magnification by predicting missing details from a sampled image. Numerous techniques have been proposed to interpolate images and produce a better and clearly defined image. However, many conventional polynomial-based interpolation methods tend to smooth or blur out image details around the edges. Although a number of different interpolation techniques are available, all of them are somewhat limited in terms of their robustness and accuracy. In this paper, an edge-directed Lagrange time delay interpolation model is developed to confront the problem. The proficiency of the new technique is compared to some of the well-known conventional interpolation techniques. The newly proposed technique is shown to provide much better resultant images compared to the other conventional interpolation methods in terms of subjective and objective evaluations of mean squared error (MSE) and structural similarity (SSIM) tests.

To evaluate metal artefact reduction (MAR) techniques from four CT vendors in hip prosthesis imaging. Bilateral hip prosthesis phantom images, obtained by using MAR algorithms for single-energy CT data or dual-energy CT (DECT) data and by monoenergetic reconstructions of DECT data, were visually graded by five radiologists using 10 image quality criteria. Comparisons between the MAR images and a reference image were performed for each scanner separately. Ordinal probit regression analysis was used. The MAR algorithms in general improved the image quality based on the majority of the criteria (up to between 8/10 and 10/10) with a statistical improvement in overall image quality (p < 0.001). However, degradation of image quality, such as new artefacts, was seen in some cases. A few monoenergetic reconstruction series improved the image quality (p < 0.004) for one of the DECT scanners, but it was only improved for some of the criteria (up to 5/10). Monoenergetic reconstructions resulted in worse image quality for the majority of the criteria (up to 7/10) for the other DECT scanner. The MAR algorithms improved the image quality of the hip prosthesis CT images. However, since additional artefacts and degradation of image quality were seen in some cases, all algorithms should be carefully evaluated for every clinical situation. Monoenergetic reconstructions were in general concluded to be insufficient for reducing metal artefacts. Qualitative evaluation of the usefulness of several MAR techniques from different vendors in CT imaging of hip prosthesis.

Recently, as the spread of ultra-high definition (UHD) display devices has become more active, considerable data bandwidth is required between the display and external memory. Compression of data can be applied to reduce memory bandwidth, but that can lead to degradation of image quality. So, in this paper, we propose a near-lossless compression algorithm that reduces memory bandwidth and minimizes image quality degradation for hardware implementation. The proposed algorithm is based on two-line memory–based prediction and transformation. Also, it improves the performance of quantization through one-dimensional (1-D) discrete cosine transform (DCT). In rate control, quantization parameters are determined using both horizontal and vertical information to improve efficiency. Finally, a partial update is implemented to enable selective decoding of images. Experimental results show that the proposed method is superior in terms of peak signal-to-noise ratio while maintaining a high compression ratio.

워터마킹은 소유권을 주장하기 위하여 워터마크라는 디지털 신호를 영상에 첨가하는 것이다. 본 논문에서는 기존의 DCT를 이용한 디지털 워터마킹 방법을 개선하여 비가시성과 견고성을 동시에 향상시키는 새로운 DCT 기반의 디지털 워터마킹 방법을 제안한다. 제안한 방법에서는 원 DCT 계수의 상대적 중요성이 워터마킹된 DCT 계수에서도 보존되며, 원 DCT 계수의 왜곡을 최소화시키는 워터마크 재정렬 방법을 이용함으로서 비가시성과 견고성을 향상시킨다. 실험을 통하여 제안한 방법은 기존의 워터마킹 방법보다 비가시성을 약 9～12[dB] 향상시키며, 다양한 공격에 대해 견고성이 월등히 우수함을 확인하였다. Watermarking is embedding a digital signal called as watermark into images to claim the ownership. In this paper, a new digital watermarking algorithm based on DCT (Discrete Cosine Transform) which enhances invisibility and robustness is proposed to improve contentional digital watermarking method using DCT. In the proposed method, it is possible to enhance invisibility and robustness using watermark reordering in which the relative significance of original DCT coefficients can be preserved in watermarked DCT coefficients, and the distortions of original DCT coefficients can be minimized. The experimental results show that the proposed method improves invisibility approximately 9～12[dB] and is more robust to various attacks than the conventional method.

Haze causes the degradation of image quality. Thus, the quality of the haze must be estimated. In this paper, we introduce a new method for measuring the quality of haze images using a no-reference scale depending on color saturation. We calculate the probability for a saturation component. This work also includes a subjective study for measuring image quality using human perception. The proposed method is compared with other methods as, entropy, Naturalness Image Quality Evaluator (NIQE), Haze Distribution Map based Haze Assessment (HDMHA), and no reference image quality assessment by using Transmission Component Estimation (TCE). This done by calculating the correlation coefficient between non-reference measures and subjective measure, the results show that the proposed method has a high correlation coefficient values for Pearson correlation coefficient (0.8923), Kendall (0.7170), and Spearman correlation coefficient (0.8960). The image database used in this work consists of 70 hazy images captured by using a special device, design to capture haze image. The experiment on haze database is consistent with the subjective experiment.

디지털 워터마킹은 저작권 보호와 멀티미디어 데이터 인증의 수단으로 사용되어 왔다. 기존의 공간영역에서의 CRT 기반 워터마킹 방법은 JPEG 압축에 취약하여, JPEG 압축에서 잘 동작하는 DCT 영역에서의 CRT 기반 워터마킹이 제안되었다. 본 논문에서는 DCT 영역에서의 향상된 CRT 기반 워터마킹 방법을 제안한다. 제안한 방법은 DCT 변환시 발생되는 rounding 오류 또는 여러 가지 공격에도 나머지들의 차에 대한 절대값의 변화를 감소시켜 견고성을 향상시킨다. 실험을 통하여 제안한 방법이 기존의 DCT 영역에서의 CRT 기반 워터마킹 방법보다 여러 가지 공격에 대하여 견고성이 향상되는 것을 확인하였다. Digital watermarking techniques have been used as one of the means for copyright protection and authentication of multimedia data. Conventional Chinese Remainder Theorem(CRT)-based spatial domain watermarking techniques do not perform well under JPEG compression. However, it is seen that the CRT-based watermarking technique in Discrete Cosine Transform(DCT) domain performs well for JPEG compression. In this paper, an improved CRT-based image watermarking method in the DCT domain is proposed. The proposed method provides better robustness which decreases changes of absolute difference of residues against rounding errors due to DCT conversion and various attacks. Experimental results show that the proposed method has a good robustness against various attacks compared with the conventional CRT-based watermarking in DCT domain.

A lot of attentions has been paid by the researchers for lossy image compression. Due to the high uses of multimedia, a high image compression ratio while keeping good image quality, is still a research issue. In this paper, we proposed an image compression using adaptive scanning, in which DWT(discrete wavelet transform) is performed to source image, DCT(discrete cosine transform) is performed to obtained DWT elements. Next, non zero quantized DCT (discrete cosine transform) coefficients are represented in less number of bits. First, the source image is divided into \(16\times 16\) grids and then DWT transformed, later the obtained elements are divided into \(8\times 8\) grids and then DCT is performed, quantized, differential encoded and an indexed vector is formed from the quantized matrix using adaptive scanning. Furthermore the indexed vector is divided into two indexed vectors namely \(nonzero\) vector and zerocount vector. The nonzero coefficients are stored in \(nonzero\) vector and the number of zeros preceding a nonzero coefficient is stored in zerocount vector. A new block is introduced to store the number of bits required to store highest value of nonzero coefficient in \(nonzero\) vector so that all the nonzero elements can be represented in that many bits rather than a fixed number of bits. The experimental results show that the proposed method has achieved more compression ratio with slight reduction in image quality as compared to existing recent methods.

Background: Guidelines for SPECT myocardial perfusion imaging (MPI) traditionally recommend a fixed tracer dose. Yet, clinical practice shows degraded image quality in heavier patients. The aim was to optimize and validate the tracer dose and scan time to obtain a constant image quality less dependent on patients' physical characteristics. Methods: 125 patients underwent Cadmium Zinc Telluride (CZT)-SPECT stress MPI using a fixed Tc-99m-tetrofosmin tracer dose. Image quality was scored by three physicians on a 4-point grading scale and related to the number of photon counts normalized to tracer dose and scan time. Counts were correlated with various patient-specific parameters dealing with patient size and weight to find the best predicting parameter. From these data, a formula to provide constant image quality was derived, and subsequently tested in 92 new patients. Results: Degradation in image quality and photon counts was observed for heavier patients for all patients' specific parameters (p<0.01). We found body weight to be the best-predicting parameter for image quality and derived a new dose formula. After applying this new body weight-depended tracer dose and scan time in a new group, image quality was found to be constant (p>0.19) in all patients. Conclusions: Also in CZT SPECT image quality decreases with weight. The use of a tracer dose and scan time that depends linearly on patient's body weight corrected for the varying image quality in CZT-SPECT MPI. This leads to better radiation exposure justification.

The aim of image fusion is to combine similar information from multiple images into a single image. The methods which are based on discrete cosine transform (DCT) of image fusion are more competent and time-saving in real-time systems using DCT based standards of still Image. The existing DCT based methods are suffering from some side effects like blurring which can reduce the quality of the output image. To address this issue, the paper proposing new method for image fusion using Gaussian pyramid in DCT domain. The pyramid fusion provides better fusion quality. The execution time is extremely reduced, compare with existing methods. This method can be used for multi model image fusion as well as fusion of complementary images. The algorithm given in proposed system is simple and easy to implement. Also, it could be used for real time applications. The performance of our method is analyzed and compared with other image fusion methods. Experimental results show that there is no difference between the result of our method and water-based image fusion result. But our algorithm is carried out in DCT domain; it is efficient in processing time and simple.

Aim and Objective:The objective of this study was to optimize the threshold for discrete cosine transform (DCT) coefficients for near-lossless compression of Tc-99 m Dimercaptosuccinic acid (DMSA) scan images using discrete cosine transformation.Materials and Methods:Two nuclear medicine (NM) Physicians after reviewing several Tc-99 m DMSA scan images provided 242 Tc-99 m DMSA scan images that had scar. These Digital imaging and communication in medicine (DICOM) images were converted in the Portable Network Graphics (PNG) format. DCT was applied on these PNG images, which resulted in DCT coefficients corresponding to each pixel of the image. Four different thresholds equal to 5, 10, 15, and 20 were applied and then inverse discrete cosine transformation was applied to get the compressed Tc-99 m DMSA scan images. Compression factor was calculated as the ratio of the number of nonzero elements after thresholding DCT coefficients to the number of nonzero elements before thresholding DCT coefficients. Two NM physicians who had provided the input images visually compared the compressed images with its input image, and categorized the compressed images as either acceptable or unacceptable. The quality of compressed images was also assessed objectively using the following eight image quality metrics: perception-based image quality evaluator, structural similarity index measure (SSIM), multiSSIM, feature similarity indexing method, blur, global contrast factor, contrast per pixel, and brightness. Pairwise Wilcoxon signed-rank sum tests were applied to find the statistically significant difference between the value of image quality metrics of the compressed images obtained at different thresholds and the value of the image quality metrics of its input images at the level of significance = 0.05.Results:At threshold 5, (1) all compressed images (242 out of 242 Tc-99 m DMSA scan images) were acceptable to both the NM Physicians, (2) Compressed image looks identical to its original image and no loss of clinical details was noticed in compressed images, (3) Up to 96.65% compression (average compression: 82.92%) was observed, and (4) Result of objective assessment supported the visual assessment. The quality of compressed images at thresholds 10, 15, and 20 was significantly better than that of input images at P < 0.0001. However, the number of unacceptable compressed images at thresholds 10, 15, and 20 was 6, 38, and 70, respectively.Conclusions:Up to 96.65%, near-losses compression of Tc-99 m DMSA images was found using DCT by thresholding DCT coefficients at a threshold value equal to 5.

At recently, the most of the digital images are stored and transferred in their compressed format using discrete cosine transform (DCT)-based compression technique. DCT is one of the most important data compression technique due to the efforts from Joint Photographic Experts Group(JPEG). Blind steganalysis means how to detect the presence of the messages that are hidden using different types of steganography algorithms and has the ability to detect new unknown steganography algorithms. This paper presents blind steganalysis technique that can reliably detect the existence of messages hidden in JPEG files. In order to save the computation and memory cost, it is desirable to have image processing operations implemented directly in the DCT domain. The proposed method is based on extracting features directly from DCT domain through the analysis of differences between DCT coefficients before and after cropping. The extracted features are prepared as input to Support Vector Machine (SVM) to classify the image as stego (image that contain secret message) or clean (image that does not contain secret message). The experiments performed show that the proposed method yields better classification accuracy compared with other related works.

COrdinate Rotation DIgital Computer (CORDIC) is commonly utilized for the computation of cosine/sine i.e., the trigonometric functions, singular value decomposition, in digital signal processing (especially in image/video processing), etc. This paper introduces an energy efficient quality tunable CORDIC architecture that computes the cosine/sine values of any required angle in real-time, and is thus well suited for real time DSP applications, especially for image or video processing applications. The proposed architecture reduces the latency and overcomes data dependency by simultaneously performing all the five iterations, that may vary depending upon the desired energy efficiency. The novelty of this architecture is that, desired quality can be achieved by selecting one out of the available three modes. In order to assess the efficacy of the suggested architecture, some benchmark images are processed using the Discrete Cosine Transform (DCT) coefficients obtained via the proposed design. Energy saving is achieved at the cost of slight acceptable degradation in the output image quality. Further, the simulation results show that the proposed architecture is 92.3%, 2.8% and 49.08% more energy efficient than the existing basic, scale-free and lookahead CORDIC architectures, respectively.