New pixel-decimation patterns for block matching in motion estimation

Motion estimation is the process which generates the motion vectors that determine how each motion compensated prediction frame is created from the previous frame. But its computational complexity poses great challenges for real time implementations. Among the different motion Estimation algorithms block matching motion estimation is the most common method of motion estimation. To minimize the search time on block matching, a simplified and efficient algorithm is very crucial for fast motion estimation process. In this paper the comparative performance of 6 different block matching algorithms are presented and compared based on the parameters of Peak Signal Noise Ratio (PSNR), Mean Absolute Difference (MAD) and Search Points per Macro block.

This paper reviews the energy efficiency of several popular block-matching motion estimation algorithms that can be used in wireless video sensor network applications. Full search motion estimation provides the best image quality but requires high computing power. Therefore, only fast search algorithms are considered for deployment in wireless video sensor networks, which generally operate in remote, battery-constrained areas. However, the image quality of fast search algorithms also needs to be considered in the comparison. In this paper, those block-matching algorithms are compared using two criteria: 1) computing cost/energy consumption, and 2) image quality. The purpose of this review is to select the most energy efficient algorithm that retains image quality and can be applied to wireless video sensor network video compression applications.

Rising numbers of computed tomography (CT) examinations worldwide have led to a focus on dose reduction in the latest developments in CT technology. Iterative reconstruction (IR) models bear the potential to effectively reduce dose while maintaining adequate image quality. To assess the impact of adaptive statistical iterative reconstruction (ASIR) technique on dose reduction and image quality in a dedicated whole body CT (WBCT) protocol for trauma patients. A total of 122 subjects with multiple trauma was prospectively included in our study. Subjects who had to undergo a WBCT following a severe trauma were randomly assigned to two different groups: Group A was examined with an ASIR protocol for the body series (n = 64), group B (n = 58) was examined using a standard filtered back projection (FBP) protocol. Image quality was assessed both quantitatively by calculating signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs) and qualitatively by two observers who evaluated image quality using a 5-point scale system. Applied dose was analyzed as CTDIvol (mGy), total DLP (mGyxcm), and effective dose (mSv). Applied dose for the body series in group A was about 23% lower than in group B (P < 0.05). SNR and CNRs for different tissues were not significantly different. Subjective image quality ratings were excellent and showed no significant difference, with a high inter-reader agreement. ASIR contributes to a relevant dose reduction without any loss of image quality in a dedicated WBCT protocol for patients with multiple trauma.

Block-matching algorithm is the most common technique applied in block-based motion estimation technique. There are several block-matching algorithm based on block-based motion estimation techniques have been developed. Full search (FS), three step search (TSS), new three step search (NTSS), diamond search (DS) and hexagon based search (HS) are the most well known block-matching algorithm. These techniques are applied to video sequences to remove the temporal redundancy for compression purposes and to gauge the motion vector estimation. In addition, the mentioned block-matching algorithms are the baseline techniques that have been used to further develop all the enhanced or improved algorithms. In order to develop the proposed methods, the baseline techniques are studied to develop the proposed algorithms. This chapter proposes modelling of fast unrestricted hexagon search (FUHS16) and unrestricted hexagon-diamond search (UHDS16) algorithms for motion vector estimation, which is based on the theory and application of block-based motion estimation. Both of these algorithms are designed using 16 × 16 block size. In particular, the motion vector estimation, quality performance, computational complexity, and elapsed processing time are emphasised. These parameters have been used to measure the experimental results. It is the aim of this study that this work provides a common framework with which to evaluate and understand block-based matching motion estimation performance. On the theoretical side, four fundamental issues are explored: (1) division of frame, (2) basic block-based matching, (3) motion vector estimation, and (4) block-matching algorithm development. Various existing block-matching motion estimation algorithms have been analysed to develop the fundamental research. Based on the theoretical and fundamental research analysis the FUHS16 and UHDS16 algorithms using 16 × 16 block-based motion estimation formulations were developed. To improve the UHDS16 algorithm, 8 × 8 block-matching technique has been tested. The 8 × 8 block-matching technique is known as UHDS8. The results show positive improvements. From an application perspective, the UHDS8 algorithm efficiently captured the motion vectors in many video sequences. For example, in video compression, the use of motion vectors on individual macro-blocks optimized the motion vector information. The UHDS8 algorithm also offers improvement in terms of image quality performance, computational complexity and elapsed processing time. Thus, this chapter offers contributions in certain areas such as reducing the mechanism of computational complexity in estimating the motion from the video sequences. In particular, the FUHS16, UHDS16 and UHDS8 algorithms were developed to estimate the motion vectors field in the video sequences. Theoretical analysis block-based matching criteria are adapted to FUHS16, UHDS16 and UHDS8 algorithms, which are based on search points technique. Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. Besides that, the UHDS8 algorithm also improves the image quality performances and the search points in terms of the computational complexity. Overall, the study shows that the UHDS8 algorithm produces better results compared to the FUHS16 and UHDS16 algorithm.

The full search block-matching algorithm is the simplest, but computationally very intensive approach. In recent years there was substantial progress in block motion estimation algorithms. Important milestones on this path were such algorithms as two-dimensional logarithmic search, three-step search, four step search, and diamond search. All these methods try to minimize the amount of search points applying sum of absolute differences (SAD) or equivalent metrics for each point. There were some works that studied partial SAD (PSAD) but mostly concentrated on a constant decimation factor. What we tried to study in this work is the performance of one of the best block matching search algorithms in combination with adaptive PSAD as a matching metric. The idea is that we use original motion estimation based on spatio-temporal correlation method, but instead of using SAD as a matching metric we use PSAD with adaptively chosen decimation factor. Our simulation results show that for high motion sequences PSNR degradation between full search and the proposed method was around 0.1-0.7 dB. The computational complexity reduction of 650-1700 times (compared with the full search) and 9 times (compared to the original method) is pretty big and may be well worth this video quality decrease. In the case of more static sequences PSNR degradation between full search and the original motion estimation method was around 0 dB. When we compare the original method with the proposed one the degradation increases to 0.1 dB. The computational complexity reduction was around 1600-1700 times (compared with the full search) and 5-7 times (compared to the original method).

Compressed sensing for reduced hardware footprint in medical ultrasound

There are several numbers famous proposed Block Matching Algorithm (BMA) in video coding technique and among it, the ARPS is a well known BMA technique that produce lower computational complexity and higher quality of the encoded video at the same time. In general, a video will has a lot of temporal redundancy among its neighborhood frames especially for a low motion video which make encoding a low motion video with smaller MB and bigger p size seemed impractical and vice versa. In this paper, the hybrid version of ARPS technique is used depending on its motion video type either low, medium, or high motion video. Basically this hybrid model works by setting the Macro Block (MB) and Search Range Size, p according to the motion type. Low motion video will be use higher size of MB and smaller size of p, medium motion has medium size of MB and p, and high or fast motion video will use smaller MB and bigger p size. The experimental result shows that by using the hybrid BMA technique, it can produce a better quality of the constructed frame and also it achieve less computational complexity at the same time.

A novel Cooperative Motion Estimation Algorithm based on Particle Swarm Optimization and its multicore implementation

MDCT angiography assessment of renal artery in-stent restenosis: Can we reduce the radiation exposure burden? A feasibility study

Council Directive 97/43/Euratom (Medical Exposure Directive) states that member States of the European Union shall promote the establishment and use of diagnostic reference levels for radio-diagnostic examinations. Dose surveys can form the basis for the establishment of diagnostic reference levels. In view of the implementation of the Medical Exposure Directive in the Netherlands, a survey of dose and image quality has been performed for posteroanterior (PA) chest radiography in 2001. In this survey, 25 participants were selected from a list of 175 Dutch hospitals, whereas in a previous PA chest survey (about 10 years ago) participation was voluntary and participants came predominantly from the south-western part of the Netherlands. For conventional screen-film PA chest radiography, the present results for patient dose and image quality are quite similar to those results from the previous survey. The fraction of conventional X-ray systems utilizing lung compensation filters has remained approximately the same. For dedicated digital chest radiography systems, image quality is better than for conventional systems, but doses vary and can assume relatively high values. The results indicate that there are still possibilities for dose reduction, without loss of image quality. The 75 percentile value of the entrance surface dose distribution is approximately 0.13 mGy.

ObjectiveTo step-wise evaluate image quality of sinogram-affirmed iterative reconstruction (SAFIRE) in reduced-dose (RD) thoracoabdominal computed tomography (CT) compared to full-dose (FD) and RD filtered back projection (FBP) in a longitudinal study.Materials and methods122 patients were included in this prospective study. 49 patients (14 men: mean age ± SD, 56±0.4 years; 35 women: 58±1.3 years) completed FD, RD1 (80%-dose) and RD2 (60%-dose) thoracoabdominal CT. Each CT dataset was reconstructed with FBP and SAFIRE. For quantitative image analysis image noise was measured in defined tissue regions. Qualitative image evaluation was performed according to the European Guidelines on Quality criteria for CT. Additionally artifacts, lesion conspicuity, and edge sharpness were assessed.ResultsCompared to FD-FBP noise in soft tissue increased by 12% in RD1-FBP and 27% in RD2-FBP reconstructions, whereas SAFIRE lead to a decrease of 28% (RD1) and 17% (RD2), respectively (all p <0.001). Visually sharp reproduction, lesion conspicuity, edge sharpness of pathologic findings, and overall image quality did not differ statistically significant between FD-FBP and RD-SAFIRE datasets. Image quality decreased in RD1- and RD2-FBP compared to FD-FBP, reaching statistically significance in RD2 datasets (p <0.001). In RD1- and RD2-FBP (p <0.001) streak artifacts were noted.ConclusionUsing SAFIRE the reference mAs in thoracoabdominal CT can be reduced by at least 30% in clinical routine without loss of image quality or diagnostic information.

A new organ-based tube current modulation (NOB-TCM) method was designed with the intent to decrease tube current by 30% over a prescribed 90° radial arc across the anterior aspect of the radiosensitive organ, without increasing tube current in the remaining radial arc. We compared a reference scan and five other dose-reducing methods with regard to effects on dose, practicality, and image quality to determine the most effective method for the reduction of the radiation dose to the eyes during CT examinations of the head. We compared the radiation doses to the eyes and physical image quality in different regions of interest for TCM and shielding scans. Three types of TCM scans were performed: longitudinal TCM, angular TCM, and NOB-TCM. A bismuth sheet and lead goggles were each applied for the shielding scan. Relative to the reference scan, the dose to the eye was reduced to 25.88% with NOB-TCM, 44.53% with lead goggles, and 36.91% with a bismuth shield. Relative to the reference scan, the mean signal-to-noise ratio (SNR) was decreased to 8.02% with NOB-TCM, 28.36% with lead goggles, and 32.95% with the bismuth shield. The SNR of the anterior region of interest was decreased to 11.89% with NOB-TCM and 87.89% with the bismuth shield. The average figure of merit was increased by 11.7% with longitudinal TCM and 13.39% with NOB-TCM, compared with the reference scan. NOB-TCM is a superior solution for head CT, including the orbital area, due to the reduction in radiation exposure without significant loss in image quality.

Cone-beam CT dacryocystography (CBCT-DCG) is a newly developed lacrimal passage imaging technique. This pilot study aimed to determine the effect of reducing tube current on image quality and radiation dose of CBCT-DCG in healthy volunteers. Thirty volunteers were randomly divided into three groups of ten. Each group of subjects underwent CBCT-DCG using a tube current of 13mA, 10mA, and 7mA respectively. The image quality of CBCT-DCG was assessed independently by two observers using three different scoring methods and compared among the groups. The effective dose was estimated and compared among the three different tube current groups. The CBCT-DCG images provided a high spatial and contrast resolution of the bony structures and the contrast medium. No significant differences were found in the image quality between different tube current groups. Compared with the 13mA group (49.44 μSv), the effective dose for 10mA group (38.40 μSv) and 7mA group (27.12 μSv) decreased by 22.33% and 45.15%, respectively. By decreasing the tube current, CBCT-DCG can be performed with a significant reduction of effective dose without loss of image quality in healthy volunteers.

To assess the impact of a method for anatomically adapted tube current variation. The resulting CT image quality was evaluated quantitatively and qualitatively. CT scans of 100 patients were performed with a constant tube current (Group 1) and another 100 patients with an anatomically adapted tube current (Group 2). The CT tube current was varied during a 360 degrees tube rotation reflecting the measured density values extracted from two perpendicular scout views. The standard deviation of densities of defined regions was measured. The image quality was ranked (1 = non-diagnostic-5 = excellent) by three radiologists. The effective tube current could be reduced by an average of 8.9% (0-20.4%). The mean tube current reduction depended on the body region: pelvis (13.2%), abdomen (8.4%) and thorax (3.3%). The image quality was not significantly reduced in Group 2. The method for anatomically adapted tube current variation leads especially in the pelvis to a significant mAs reduction without considerable loss of image quality.

The image quality of pseudophakic eyes with intraocular lenses in high myopia was studied by applying geometric and wave optics. Two types of intraocular lenses (IOL) were compared—one that was meniscus shaped and the other either planoconcave or planoconvex [bending factor (X)511]. A geometric study of image quality was used to analyze the transverse spherical aberration (TA) and the chromatic aberration (chromatic difference of the blur circles, CDBC). The loss of image quality and visual acuity increases as the TA and CDBC increase. The polychromatic modulation transfer function (MTF) was obtained using the point-spread function (PSF), taking into account spherical aberration and defocus coefficients. Finally, for chromatic and spherical aberrations and polychromatic MTF, the type of IOL that would best improve image quality for a given patient can be established.