An automatic region-based video sequence codec based on fractal compression

In order to improve the performance of fractal video coding, we explore a novel fractal video sequences codec with automatic region-based functionality. To increase the quality of decoding image, intra frame coding, deblocking loop filter and sub-pixel block matching are applied to the codec. An efficient searching algorithm is used to increase the compression ratio and encoding speed. Automatic region-based fractal video sequences coding reduces coding stream greatly. Experimental results indicate that the proposed algorithm is more robust, and provides much less encoding time and bitrate while maintaining the quality of decompression image than the conventional CPM/NCIM method and other related references. We compare the proposed algorithm with three algorithms in Refs. [24], [25], [26], and the results of all these four algorithms are compared with H.264. The bitrate of the proposed algorithm is decreased by 0.11% and the other algorithms are increased by 4.29%, 6.85% and 11.62%, respectively. The average PSNR degradations of the four algorithms are 0.71 dB, 0.48 dB, 0.48 dB and 0.75 dB. So the bitrate of the proposed algorithm is decreased and the other algorithms are increased. At the meantime the compression time is reduced greatly, about 79.19% on average. The results indicate that, on average, the proposed automatic region-based fractal video sequences coding system can save compression time 48.97% and bitrate 52.02% with some image quality degradation in comparison with H.264, since they are all above 32 dB and the human eyes are insensitive to the differences.     

No-reference analysis of decoded MPEG images for PSNR estimation and post-processing

We propose no-reference analysis and processing of DCT (Discrete Cosine Transform) coded images based on estimation of selected MPEG parameters from the decoded video. The goal is to assess MPEG video quality and perform post-processing without access to neither the original stream nor the code stream. Solutions are presented for MPEG-2 video. A method to estimate the quantization parameters of DCT coded images and MPEG I-frames at the macro-block level is presented. The results of this analysis is used for deblocking and deringing artifact reduction and no-reference PSNR estimation without code stream access. An adaptive deringing method using texture classification is presented. On the test set, the quantization parameters in MPEG-2 I-frames are estimated with an overall accuracy of 99.9% and the PSNR is estimated with an overall average error of 0.3 dB. The deringing and deblocking algorithms yield improvements of 0.3 dB on the MPEG-2 decoded test sequences.     

Ripplet: A new transform for image processing

Efficient representation of images usually leads to improvements in storage efficiency, computational complexity and performance of image processing algorithms. Efficient representation of images can be achieved by transforms. However, conventional transforms such as Fourier transform and wavelet transform suffer from discontinuities such as edges in images. To address this problem, we propose a new transform called ripplet transform. The ripplet transform is a higher dimensional generalization of the curvelet transform, designed to represent images or two-dimensional signals at different scales and different directions. Specifically, the ripplet transform allows arbitrary support c and degree d while the curvelet transform is just a special case of the ripplet transform (Type I) with c = 1 and d = 2. Our experimental results demonstrate that the ripplet transform can provide efficient representation of edges in images. The ripplet transform holds great potential for image processing such as image restoration, image denoising and image compression.     

Surface reconstructions on Sb-irradiated GaAs(0 0 1) formed by molecular beam epitaxy

Reconstructed surfaces on Sb-irradiated GaAs(0 0 1) formed by molecular beam epitaxy have been studied by in-situ scanning tunneling microscopy (STM). The reflection high-energy electron diffraction patterns showed (2×3) [or weak (4×3)] structure. The step density was about five times higher than that of GaAs(0 0 1)-c(4×4) surface. It was found that there were swinging dimer rows along to the [1 1¯ 0] direction, which seemed not to consist of a specified reconstruction. We proposed two (2×3)-structure models for these swinging dimers. By first-principles calculation, we found that the proposed models were stable and with energy difference was 0.17 eV, indicating the coexistence of the two structures. Moreover, we proposed three (4×3) reconstruction models based on these (2×3) models. The electron counting rule was applied for these models, indicating that there was an excessive amount of electrons. By two bias-alternative STM images, it was found that the many spots appear only in empty-state. These might be segregated Ga or Sb cluster and strongly relate to the excessive amount of electrons.     

All-digital thermal distribution measurement on field programmable gate array using ring oscillators

In this paper, a digital method for transient temperature distribution measurement of field programmable gate array (FPGA)-based systems is proposed. The smart thermal sensors used rely on correspondence between the delay and temperature in a ring oscillator. The tested temperature was converted into a time signal with a thermally-sensitive width. The output frequency is read out by a counter with a scan path, and then, transited to PC by a Universal Serial Bus (USB) interface. We capture the infrared images of the FPGA chip by infrared camera. The images were compared with the thermal map of the die constructed using an array of sensors. The tested temperature error varies by less than 1.6 °C in the range from 20 °C to 90 °C, and the maximum sampling rate is 330 Hz.     

Chromatic dispersion estimation methods using polynomial fitting in PDM-QPSK or other multilevel-format coherent optical systems

We propose a polynomial fitting algorithm based method for non-data-aided chromatic dispersion (CD) estimation in single carrier (SC) coherent optical systems with arbitrary modulation formats, and compare it with our previously proposed CD estimation method which is also based on the polynomial fitting algorithm but requires special modulation formats thus is a data-aided CD estimation method for systems with PDM-QPSK or other multilevel modulation formats. For the data-aided CD estimation method, an extra chirp-free OOK signal is transmitted. The curve of the average phase at the frequency ± f as a function of the frequency f is measured at the coherent receiver. The accumulated CD is then estimated with a polynomial fitting algorithm. In the simulation of a 50 Gbaud 50%-RZ OOK system through 12.5 × 80 km standard single mode fiber (SSMF), the estimation errors are within ± 50 ps/nm in 20 tests when the launch power is from −5 dBm to −1 dBm. Non-data-aided CD estimation for arbitrary modulation formats is achieved by measuring the differential phase between frequency f ± f_s/2 (f_s is the symbol rate) in digital coherent receivers. The estimation errors are within ± 200 ps/nm, in a 50 Gbaud PDM-QPSK system through 10 × 80 km SSMF with the launch power from −3 dBm to −1 dBm. The estimation accuracy can be potentially improved by averaging multiple results. The data-aided CD estimation method has an inherently bigger estimation range than that of the newly proposed non-data-aided method, while the newly proposed non-data-aided method can tolerate a much larger frequency offset between the transmitter and the local oscillator. These methods are promising for future optical fiber networks with dynamic optical routing and coherent detection.     

Sub-micron imaging on high-topography wafers using spray coating and projection lithography

We propose a method to image inside deep trenches (50 μm) using spray-coated resist and the ASML PAS 5500/100 system with the new functionality multi-step imaging. Multi-step imaging allows extending the focus offset range of the PAS 5500/100 system from ±30 μm to ±200 μm. Isolated trenches and contact holes were both imaged inside the deep trenches and on the surface of the wafer to study the versatility of the new functionality. A resolution of 700 nm in 3 μm thick photoresist, at the bottom of 50 μm deep, 200 μm wide trench, was obtained with this process. Finally, multi-focus exposure that consists in exposing the same image several times at various focus offsets was performed in order to image thick photoresist on high topographic substrates.     

Near optimal scheduling of data aggregation in wireless sensor networks

Due to the large-scale ad hoc deployments and wireless interference, data aggregation is a fundamental but time consuming task in wireless sensor networks. This paper focuses on the latency of data aggregation. Previously, it has been proved that the problem of minimizing the latency of data aggregation is NP-hard [1]. Many approximate algorithms have been proposed to address this issue. Using maximum independent set and first-fit algorithms, in this study we design a scheduling algorithm, Peony-tree-based Data Aggregation (PDA), which has a latency bound of 15R + Δ ? 15, where R is the network radius (measured in hops) and Δ is the maximum node degree. We theoretically analyze the performance of PDA based on different network models, and further evaluate it through extensive simulations. Both the analytical and simulation results demonstrate the advantages of PDA over the state-of-art algorithm in [2], which has a latency bound of 23R + Δ ? 18.     

Hardware implementation and validation of the fast variable block size motion estimation architecture for H.264/AVC

Block matching motion estimation is the heart of video coding system. It leads to a high compression ratio, whereas it is time consuming and calculation intensive. Many fast search block matching motion estimation algorithms have been developed in order to minimize search positions and speed up computation but they do not take into account how they can be effectively implemented by hardware. In this paper, we propose an efficient hardware architecture of the fast line diamond parallel search (LDPS) algorithm with variable block size motion estimation (VBSME) for H.264/AVC video coding system. The design is described in VHDL language, synthesized to Altera Stratix III FPGA and to TSMC 0.18 μm standard-cells. The throughput of the hardware architecture reaches a processing rate up to 78 millions of pixels per second at 83.5 MHz frequency clock and uses only 28 kgates when mapped to standard-cells. Finally, a system on a programmable chip (SoPC) implementation and validation of the proposed design as an IP core is presented using the embedded video system.     

A 1-V, 1.2-mA fully integrated SoC for digital hearing aids

Both power and size are very important design issues for hearing aids. This paper proposes a fully integrated low-power SoC for today׳s digital hearing aids. The SoC integrates all the audio processing elements on single chip, including the analog front-end, digital signal processing (DSP) platform and class-D amplifier. Also, the low-dropout voltage regulators and internal clock generator are both integrated to minimize the system overall size. The 24-bit DSP platform comprises an application-specific instruction-set processor and several dedicated accelerators to achieve a trade-off between flexibility and power efficiency. Three critical hearing-aid algorithms (wide dynamic range compression, noise reduction and feedback cancellation) are performed by the low-power accelerators. The proposed SoC has been fabricated in SMIC 130 nm CMOS technology. The measurement results show that the analog front-end has up to 88 dB signal-to-noise ratio. And the DSP platform consumes about 0.86 mA current at 8 MHz clock frequency when executing the three algorithms. The total current consumption of SoC is only 1.2 mA at 1 V supply. In addition, the acoustic test results indicate that the SoC is one promising candidate for hearing-aid manufacturers.     

PMOSFET anti-fuse using GIDL-induced-HEIP mechanism

We propose a novel electrical fuse (e-fuse) program procedure using shallow trench isolation (STI) edge trapping mechanism of PMOSFET by applying AC pulses. We obtained flash characteristics using conventional PMOSFET structure, when injected AC pulse on source node under off-state condition (V_g = high, V_d = low). In order to verify programming, double hump characteristics and thermal conduction analysis are introduced.     

Highly enhanced light extraction from organic light emitting diodes with little image blurring and good color stability

We report a highly enhanced light extraction from a top emission organic light emitting diode with little image blurring and color variation with viewing angle. Direct integration of a high refractive index micro lens array on the top of the transparent indium zinc oxide top electrode of a green phosphorescent OLED showed a significant enhancement of light extraction to get EQE of 44.7% from 27.6%, the power efficiency of 134.7 lm/w from 85.9 lm/W and the current efficiency of 217.2 cd/A from 120.7 cd/A without image blurring. In addition, the device showed excellent color stability on viewing angle with Commission Internationale de l’Eclairage (CIE) coordinate of Δx = 0.01, Δy = 0.01 as the viewing angle varied from 0° to 60°.     

A novel image restoration scheme based on structured side information and its application to image watermarking

This paper presents a new image restoration method based on a linear optimization model which restores part of the image from structured side information (SSI). The SSI can be transmitted to the receiver or embedded into the image itself by a digital watermarking technique. In this paper we focus on a special type of SSI for digital watermarking where the SSI is composed of mean values of 4×4 image blocks which can be used to restore manipulated blocks. Different from existing image restoration methods for similar types of SSI, the proposed method minimizes image discontinuity according to a relaxed definition of smoothness based on a 3×3 averaging filter of four adjacent pixel value differences, and the objective function of the optimization model has a second regularization term corresponding to a second-order smoothness criterion. Our experiments on 100 test images showed that given complete information of the SSI, the proposed image restoration technique can outperform the state-of-the-art model based on a simple linear optimization model by around 2 dB in terms of an average Peak Signal-to-Noise Ratio (PSNR) value and around 0.04 in terms of a Structural Similarity Index (SSIM) value. We also tested the robustness of the image restoration method when it is applied to a self-restoration watermarking scheme and the experimental results showed that it is moderately robust to errors in SSI (which is embedded as a watermark) caused by JPEG compression (the average PSNR value remains above 16.5 dB even when the JPEG QF is 50), additive Gaussian white noises (the average PSNR value is approximately 18.4 dB when the noise variance σ² is 10) and image rescaling assuming the original image size is known at the receiver side (e.g. the average PSNR value is approximately 19.6 dB when the scaling ratio is 1.4).     

Fuzzy quantization based bit transform for low bit-resolution motion estimation

This study proposes a novel fuzzy quantization based bit transform for low bit-resolution motion estimation. We formalize the procedure of bit resolution reduction by two successive steps, namely interval partitioning and interval mapping. The former is a many-to-one mapping which determines motion estimation performance, while the latter is a one-to-one mapping. To gain a reasonable interval partitioning, we propose a non-uniform quantization method to compute coarse thresholds. They are then refined by using a membership function to solve the mismatch of pixel values near threshold caused by camera noise, coding distortion, etc. Afterwards, we discuss that the sum of absolute difference (SAD) is one of the fast matching metrics suitable for low bit-resolution motion estimation in the sense of mean squared errors. A fuzzy quantization based low bit-resolution motion estimation algorithm is consequently proposed. Our algorithm not only can be directly employed in video codecs, but also be applied to other fast or complexity scalable motion estimation algorithms. Extensive experimental results show that the proposed algorithm can always achieve good motion estimation performances for video sequences with various characteristics. Compared with one-bit transform, multi-thresholding two-bit transform, and adaptive quantization based two-bit transform, our bit transform separately gains 0.98 dB, 0.42 dB, and 0.24 dB improvement in terms of average peak signal-to-noise ratio, with less computational cost as well.     

View-spatial–temporal post-refinement for view synthesis in 3D video systems

Depth image based rendering is one of key techniques to realize view synthesis for three-dimensional television and free-viewpoint television, which provide high quality and immersive experiences to end viewers. However, artifacts of rendered images, including holes caused by occlusion/disclosure and boundary artifacts, may degrade the subjective and objective image quality. To handle these problems and improve the quality of rendered images, we present a novel view-spatial–temporal post-refinement method for view synthesis, in which new hole-filling and boundary artifact removal techniques are proposed. In addition, we propose an optimal reference frame selection algorithm for a better trade-off between the computational complexity and rendered image quality. Experimental results show that the proposed method can achieve a peak signal-to-noise ratio gain of 0.94 dB on average for multiview video test sequences when compared with the benchmark view synthesis reference software. In addition, the subjective quality of the rendered image is also improved.     

Aligned and non-aligned double JPEG detection using convolutional neural networks

Due to the wide diffusion of JPEG coding standard, the image forensic community has devoted significant attention to the development of double JPEG (DJPEG) compression detectors through the years. The ability of detecting whether an image has been compressed twice provides paramount information toward image authenticity assessment. Given the trend recently gained by convolutional neural networks (CNN) in many computer vision tasks, in this paper we propose to use CNNs for aligned and non-aligned double JPEG compression detection. In particular, we explore the capability of CNNs to capture DJPEG artifacts directly from images. Results show that the proposed CNN-based detectors achieve good performance even with small size images (i.e., 64 × 64), outperforming state-of-the-art solutions, especially in the non-aligned case. Besides, good results are also achieved in the commonly-recognized challenging case in which the first quality factor is larger than the second one.     

Correlation estimation from compressed images

This paper addresses the problem of correlation estimation in sets of compressed images. We consider a framework where the images are represented under the form of linear measurements due to low complexity sensing or security requirements. We assume that the images are correlated through the displacement of visual objects due to motion or viewpoint change and the correlation is effectively represented by optical flow or motion field models. The correlation is estimated in the compressed domain by jointly processing the linear measurements. We first show that the correlated images can be efficiently related using a linear operator. Using this linear relationship we then describe the dependencies between images in the compressed domain. We further cast a regularized optimization problem where the correlation is estimated in order to satisfy both data consistency and motion smoothness objectives with a Graph Cut algorithm. We analyze in detail the correlation estimation performance and quantify the penalty due to image compression. Extensive experiments in stereo and video imaging applications show that our novel solution stays competitive with methods that implement complex image reconstruction steps prior to correlation estimation. We finally use the estimated correlation in a novel joint image reconstruction scheme that is based on an optimization problem with sparsity priors on the reconstructed images. Additional experiments show that our correlation estimation algorithm leads to an effective reconstruction of pairs of images in distributed image coding schemes that outperform independent reconstruction algorithms by 2–4 dB.     

Direct transfer patterning on three dimensionally deformed surfaces at micrometer resolutions and its application to hemispherical focal plane detector arrays

Formation of high performance organic electronic devices on three dimensionally deformed surfaces is severely constrained by the tensile stresses and shear that are introduced during the deformation process. Here, we overcome these limitations to demonstrate the direct transfer of unstrained metals via cold welding onto preformed, 1.0 cm radius plastic hemispheres with micrometer scale feature resolutions to realize 10 kilopixel organic photodetector focal plane arrays (FPAs) that mimic the size, function, and architecture of the human eye. The passive matrix FPA consists of (40 μm)² organic double heterojunction photodetectors with response extending across the visible spectrum. The detector dark current density is 5.3 ± 0.2 μA/cm² at −1 V bias, and with a peak external quantum efficiency of 12.6 ± 0.3% at a wavelength of 640 nm. The photodetector impulse response was 20 ± 2 ns, making the FPA suitable for video recording applications. The measured dynamic range allows for 7 bit image resolution, and the FPA is used to create a simple image. This demonstration significantly extends the ability to transfer active electronic devices that has previously only been demonstrated on planar substrates.     

Power assignment problems in wireless communication: Covering points by disks,reaching few receivers quickly,and energy-efficient travelling salesman tours

In this paper, we present approximation algorithms for a variety of problems occurring in the design of energy-efficient wireless communication networks. We first study the k-station network problem, where for a set S of stations and some constant k, one wants to assign transmission powers to at most k senders such that every station in S can receive a signal from at least one sender. We give a (1 + ?)-approximation algorithm for this problem. The second problem deals with energy-efficient networks, allowing bounded hop multicast operations, that is given a subset C of the stations S and a designated source node s ∈ S, we want to assign powers to the sending stations, such that every node in C can be reached by a transmission from s within k hops. For this problem, we provide an algorithm which runs in time linear in ∣S∣. The last problem deals with a variant of the non-metric TSP problem where the edge costs correspond to the Euclidean distances to the power of some α ? 1; this problem is motivated by data aggregation schemes in wireless sensor networks. We provide a simple constant approximation algorithm, which improves upon previous results when 2 ? α ? 2.7.     

Hardware implementation of a spatio-temporal average filter for real-time denoising of fluoroscopic images

An electronic system for the real-time denoising of fluoroscopic images is proposed in this paper. Fluoroscopic devices use X-rays to obtain real-time moving images of patients and support many surgical interventions and a variety of diagnostic procedures. In order to avoid risks for the patient, X-ray intensity has to be kept acceptably low during the clinical applications. This implies that fluoroscopic images are corrupted by large quantum noise (Poisson-distributed). Real-time noise reduction can offer a better visual perception to doctors and possible further reductions of the dose.The proposed circuit implements a spatio-temporal filter optimized for the removal of the quantum noise while preserving video edges and the prompt response of the image to the introduction of new features in the field. The filter incorporates information on the dependence of the standard deviation of the noise on the local brightness of the image and performs a conditioned average operation.The proposed circuit is implemented on FPGA (Field Programmable Gate Array) device allowing the real time elaboration of video streams composed by frames with 1024×1024 pixel and uses an external DDR2 (Double Data Rate 2) memory for the storage and the reuse of the fluoroscopic frames needed by the filter.When implemented on StratixIV-GX70 FPGA the circuit is able to process up to 49 fps (frames per second) while using 80% of the logic resources of the FPGA.