nils-herrmann/clean_scirepeval huggingface dataset:
A hybrid edge-preserving image smoothing scheme for noise removal

In this paper, we propose a new image denoising scheme that is an integration of a content-adaptive guided filter and a collaborative Wiener filter. The proposed scheme consists of two steps. First a content-adaptive guided filter, which smoothes image based on spatial similarity within a local window, is applied. The content-adaptive guided filter can efficiently preserve edges while smoothing noise. A preliminary estimation of noise-free image can be obtained by the content-adaptive guided filter. In the second step, a patch-grouping based collaborative Wiener filter is adopted to exploit non-local similarity, and outputs final denoised image. Compared to the state-of-the-art denoising scheme, BM3D, the proposed method is more efficient in computation. Moreover, simulation results have shown that the proposed method can achieve comparable PSNR values and better visual quality on denoising of textural images.
A local intensity adaptive structural similarity index

Existing structural similarity (SSIM) index comprises of one term on luminance comparison and the other term on contrast and structure comparison. In this paper, the SSIM index is first improved by introducing three weighting factors to the second term such that it is adaptive to local intensities of two images to be compared. The improved SSIM (iSSIM) index is further extended for two images with possibly different exposures. Experimental results show that the proposed indices are more robust to large intensity changes of two images from the same scene and more sensitive to two images from different scenes than the existing SSIM index.
Chaotic cryptosystem with high sensitivity to parameter mismatch

In this brief, we present a new sufficient condition for the stabilization and the synchronization of Chua's circuit. The Chua's circuit is used in our chaotic secure cryptosystem and the relaxed stability condition enables us to obtain a larger bound on the impulsive interval, which leads to a higher efficiency in bandwidth utilization. In the proposed system, we introduce the concept of a magnifying glass to enlarge and observe minor parameter mismatch and hence to increase the sensitivity and the security level of the cryptosystem. We use speech transmission as an example to illustrate that the proposed cryptosystem can achieve an excellent encryption effect and that it is sensitive to parameter mismatch.
Anti-ghost of differently exposed images with moving objects

In a typical image synthesis where multiple differently exposed images are captured for processing, it is important to design an anti-ghost algorithm so as to prevent ghosting artifacts from appearing in the final image. An anti-ghost algorithm is usually composed of a detection module and a correction module. In this paper, a new detection module is proposed to detect non-consistent pixels of all input images without predefining any initial reference image. The proposed module is suitable when an interactive mode is desired. In addition, a bidirectional approach is introduced to correct the non-consistent pixels in the correction module. Compared with existing unidirectional correction methods, the proposed bidirectional correction approach uses information from two adjacent images of a detected image to correct its non-consistent pixels. This leads to a quality improvement in the final image.
A Fully Cooperative Network

A charging scheme and a flow control scheme are designed for a fully cooperative network by using a new concept of generalized Nash equilibrium that is based on an assumption that each player is wise and intends to minimize instead of maximize his/her expected utility payoff (or maximize the opponent's utility payoff). In our scheme, each link will increase its price when the system is under-loaded, and decrease its price when the system is over-loaded. On the other hand, the sending rate of each source is a monotonous non-decreasing function of the price, i.e., each source will increase transmission rate when the price does not fall and decrease transmission rate when the price falls. Clearly, our scheme is different from existing network framework that is based on the conventional microeconomic system. With our scheme, the network is harmonious in the sense that besides all sources cooperate with each other, sources and links are also cooperative with each other. This distinguishes our scheme from existing cooperative scheme in the sense that in the existing schemes, only sources are cooperative with each other. With our scheme, each link has an incentive to increase its capacity because it can get more profit. This is very helpful for the evolution of the Internet
A novel rate control scheme for video over the internet

In this paper, we present a rate control scheme for video over the Internet by adopting a fluid-flow traffic model and a new quadratic rate-distortion (R-D) model. Some simple control theory rather than a heuristic method is used to compute the target rate for each frame. Our scheme is better than some other existing schemes in the sense that our scheme can adapt itselfin time to the variation of channel bandwidth, the number of skipped frames is reduced and the average PSNR is usually improved. Thus, our scheme is very attractive for video over the Internet.
Camera noise model-based motion detection and blur removal for low-lighting images with moving objects

It is well known that modern CCD/CMOS digital cameras produce color images contaminated by mixed photon-electronic noise, which is a mixture of signal-dependent optical photon noise and signal-independent electronic noise. In statistical, variance of the mixed noise is a line function of mean intensity on the pixel. Based on this camera variance-mean model, we propose a fast and robust approach to generate a high quality image from a pair of noisy/blurred low-lighting images with moving objects along any directions. More precisely, camera noise variance model is employed to separate the effects of noise from moving objects on the images, followed by BM3D denoising method to reduce the noise of identified moving objects in the noisy image. Then motion blur in the blurred image is removed by a patching method, which is robust to object movements along any directions. We validate the effectiveness of our proposed approach on real images with moving objects in this paper.
A new chaotic secure communication system

The paper proposes a digital chaotic secure communication by introducing a magnifying glass concept, which is used to enlarge and observe minor parameter mismatch so as to increase the sensitivity of the system. The encryption method is based on a one-time pad encryption scheme, where the random key sequence is replaced by a chaotic sequence generated via a Chua's circuit. We make use of an impulsive control strategy to synchronize two identical chaotic systems embedded in the encryptor and the decryptor, respectively. The lengths of impulsive intervals are piecewise constant and, as a result, the security of the system is further improved. Moreover, with the given parameters of the chaotic system and the impulsive control law, an estimate of the synchronization time is derived. The proposed cryptosystem is shown to be very sensitive to parameter mismatch and hence the security of the chaotic secure communication system is greatly enhanced.
Hybrid Patching for a Sequence of Differently Exposed Images With Moving Objects

It is very challenging to synthesize a high dynamic range (HDR) image from multiple differently exposed low dynamic range images when there are moving objects in the images. This is due to the fact that the moving objects will cause ghosting artifacts to appear in the synthesized HDR image. To prevent such artifacts, a patching algorithm is required to correct motion regions such that all the moving objects are synchronized in the differently exposed images. In this paper, a new optimization problem is formulated to correct the motion regions of the multiple differently exposed images by considering both spatial and temporal consistencies. The resultant scheme is a hybrid patching scheme composed of a correction method which is an intensity mapping function at pixel level, and a hole-filling method that uses block-level template matching. The proposed patching scheme is not only robust to large intensity changes in these input images, but also at regions that are over-or under-exposed. Experimental results show that the proposed method is able to prevent ghosting artifacts from appearing in the final synthesized HDR image.
Detail-Enhanced Multi-Scale Exposure Fusion

Multi-scale exposure fusion is an effective image enhancement technique for a high dynamic range (HDR) scene. In this paper, a new multi-scale exposure fusion algorithm is proposed to merge differently exposed low dynamic range (LDR) images by using the weighted guided image filter to smooth the Gaussian pyramids of weight maps for all the LDR images. Details in the brightest and darkest regions of the HDR scene are preserved better by the proposed algorithm without relative brightness change in the fused image. In addition, a new weighted structure tensor is introduced to the differently exposed images and it is adopted to design a detail extraction component for the proposed fusion algorithm, such that users are allowed to manipulate fine details in the enhanced image according to their preference. The proposed multi-scale exposure fusion algorithm is also applied to design a simple single image brightening algorithm for both low-light imaging and back-light imaging.
Adaptive unequal error control for video over the Internet

We propose an adaptive unequal error protection scheme to help protect a video stream over the Internet. The data partition approach and the resynchronization marker are applied to generate two types of packets with different importance. Our scheme is very adaptive to network traffic conditions and can be easily implemented via software. With the proposed scheme, more protection is provided for the more important packets. The final quality can therefore be improved at a higher packet loss ratio.
Robust stability of a class of hybrid nonlinear systems

We analyze the discrete behavior to identify all kinds of cycles of hybrid nonlinear systems and then study the continuous behavior along each kind of cycle. Based on these analysis, we construct some continuous functions to bound Lyapunov functions along all subsystems and identify a subsequence of time points where the Lyapunov functions are non-increasing. We use these results to derive some new sufficient conditions for the robust stability of a class of hybrid nonlinear systems with polytopic uncertainties. These conditions do not require the Lyapunov functions to be non-increasing along each subsystem nor the whole sequence of the switching. Furthermore, they do not require the knowledge of continuous trajectory.
Quadratic optimization based small scale details extraction

In many image processing problems, it is required to extract small scale details from an image or a set of images. In this paper, we introduce a new framework for extracting small scale details from a single input image or a set of input images. We then show how to apply the framework to address several important problems in the field of image processing including tone mapping of high dynamic range images, de-noising of a non-flash image with a pair of non-flash and flash images, as well as details enhancement via multi-light images and a single input image. Experimental results show that the proposed framework outperforms existing methods.
Sufficient conditions for almost sure stability of jump linear systems

This paper derives less conservative conditions for almost-sure stability of jump linear systems by using the stochastic version of Lyapunov's second method. To ensure the required stability, the Lyapunov function is only required to be nonincreasing along each of the specially organized subsequences of "jumgings". This allows one to handle the case where some or even all subsystems are unstable and provides more choices of Lyapunov functions.
Globally exponential stabilization of switched nonlinear systems with arbitrary switchings

Switched nonlinear systems (SNS) are control systems that involve both continuous and discrete dynamics. The design of switched nonlinear systems is mainly composed of two parts. One is to design a smooth controller for each continuous subsystem such that each subsystem satisfies certain given requirements, the other is to define a switching law for the continuous controllers such that the overall switched nonlinear system achieves some given specifications. The continuous controllers, together with the corresponding switching law, form a switched controller. In this paper, we consider the problem of globally exponential stabilization of switched nonlinear systems with arbitrary and infinite number of "switchings". We handle both the case where the switchings of the system coincide exactly with the switchings of the controllers and the case where the switchings of the system do not coincide exactly with the switchings of controllers. An SNS in the first case and in the second case is called a synchronous SNS and an asynchronous SNS, respectively. Methods are presented to design switched controllers in both cases. Some sufficient conditions are derived to globally exponentially stabilize the system in both cases. However, emphasis is placed on the second case.
Impact of climate warming on drought characteristics of summer maize in North China Plain for 1961–2010

North China Plain (NCP) is the major grain production region of the rain-fed summer maize and its natural climatic conditions play a decisive role in maize growth process. In this study, we focused on temporal-spatial characteristics of drought during maize growth period (June-September), and wanted to access the impact of climatic warming trend on summer maize drought during its growing season in NCP. To understand these questions, we used monthly mean air temperature and monthly precipitation data of 27 stations in NCP from 1961-2010. First, jumping points of mean temperature and precipitation in maize growth period were fixed by Mann-Kendall test method. Second, the self-calibrating Palmer Drought Severity Index (SC-PDSI) was used to calculate the drought level and the drought distribution characters were captured by empirical orthogonal function (EOF). Third, analyses of drought occurrence probability were conducted under two scenarios, i.e. one was actual observations, and another consisted of monthly actual precipitation for each year and past 50 years average of monthly mean temperature. Results showed that mean temperature and total precipitation in maize growth period were in a slightly decreasing trend before 1996, which was the jumping time point of mean temperature. After 1996, mean temperature of maize growth period was higher than the 50 years average of 0.4°C-1.0°C, while the trend of total precipitation in maize growth period was transferred from decreasing to increasing. The spatial character of drought occurrence in maize growth period showed consistency in NCP, and the most prone to drought and the hardest drought area was located in Henan Province. Drought occurrence probability increased by an average of 10.1% due to climate warming appeared since mid-1990s, and above severe drought increased in an average of 9% at the same time. These increase extent were higher than that of the decreased ones before the mid-1990s when temperature was lower than 50 years average. In addition, the proportion of above severe drought occurrence also rose with the climate warming. Therefore, the warming trend would have a significant effect on drought occurrence of summer maize in NCP.
A novel joint rate control scheme for the coding of multiple real time video programs

The objective of joint rate control is to achieve a better and more uniform picture quality by exploiting the complexity of each program. In this paper, a novel joint rate control scheme is presented for real time coding of multiple video programs. In our scheme, the total available channel bandwidth is firstly assigned to each program in proportion to its information content. A novel control scheme, which is adaptive to the variation of distributed bandwidth, is then presented in our design to determine quantization parameters and the number of skipping frames for each program. As a result, the proposed scheme can be considered as a "look current" scheme, which outperforms many existing ones in terms of coding complexity and video quality.
Accurate H.264 rate control with new rate-distortion models

H.264 rate control is an interesting problem that has motivated numerous possible solutions. The challenge lies in determining a quantization parameter Qp that will be used for both the rate-distortion (R-D) optimization process and the quantization of transform coefficients. In this work, we attempt to achieve effective rate control with a different approach. By modelling the relationships of distortion, texture bits, non-texture bits and Qp, we can derive the Qp required for both R-D optimization and quantization through Lagrangian optimization. From experiments with several video sequences, we found that our rate control scheme is capable of effective rate control with minimal model updates during encoding. The proposed rate control scheme adapts quickly to the characteristic of the source data and is particularly effective at controlling the rate of videos with high and unpredictable motion content.
Motion compensated temporal filtering with optimal temporal distance between each motion compensation pair

A novel motion compensated temporal filtering (MCTF) scheme is proposed in this paper by properly using forward and backward motion compensations. The mean, the second moment and the maximum value for the temporal distance of all motion compensation pairs (MCPs) in a group of frames (GOF) are minimized such that the number of "unconnected" pixels is minimized. The overall coding efficiency is improved by up to 1.5 dB when compared to the scheme provided in [?] while the total number of motion estimation remains the same.
Color Contrast-Preserving Decolorization

Decolorization is to convert a color image into a gray scale image while preserve image features such as salient structure and chrominance contrast. The sign of the color contrast is crucial for the decolorization algorithm and is usually determined in existing works by giving a strictly defined color order or two-mode weak order. In this paper, a fast computation on color order is achieved via a simple global mapping which is introduced in a linear parametric model using an extended structure transfer filter. The values of the parameters are obtained via an elegant approximation method. A local decolorization algorithm is finally designed on the basis of the global linear mapping so that both color and spatial information are preserved robustly and accurately. Experimental results show that the proposed decolorization algorithms obtain a good performance among existing quality metrics for the decolorization. In addition, the proposed global decolorization algorithm is friendly to mobile devices with the limited computational resource.
Customer Adaptive Combined SNR and Spatial Scalability

A new type of region of interest (ROI) is proposed in this paper for scalable video coding with the whole region be the combined SNR and spatial scalability, and a sub-region be a specific choice of spatial resolution and bit rate range. The ROI is applied to design a combined SNR and spatial scalability scheme that is adaptive to customer composition such that an optimal customer oriented scalable tradeoff (COST) can be achieved. The profit can thus be maximized
Adaptive rate control for real time video coding process

The demand for a live video over the Internet and wireless links has grown rapidly. Therefore, it is very important to design a video compression system adaptive to variable network conditions. We propose an adaptive rate control scheme, which can be applied to design a video compression system adaptive to the available channel bandwidth. This scheme is better than existing schemes in the sense that the coding process is adaptive to the network condition, fewer frames are skipped, and the average PSNR is usually improved.
A directional field based fast intra mode decision algorithm for H.264 video coding

The H.264 video coding standard can achieve considerably higher coding efficiency than previous standards. In order to achieve this, a robust rate-distortion optimization (RDO) technique is employed to select the best coding mode for each macroblock. As a result. the encoder complexity is increased considerably. This paper presents a directional field based fast intra mode decision algorithm to improve the encoder's efficiency. Prior to intra prediction, the directional field is calculated for all the block size to decide the dominant edge direction in the blocks. Based on the edge direction information, only a small number of prediction modes are chosen for RDO calculation. Experimental results show that the fast intra mode decision algorithm increases the speed of intra coding significantly with negligible loss of PSNR
Half-quadratic regularization based de-noising for high dynamic range image synthesis

It is possible to synthesis a high dynamic range (HDR) image by combining differently exposed low dynamic range (LDR) images of the same scene into one single image. For an HDR scene under low light condition, captured LDR images tend to be noisy, and the noise could usually be amplified during the synthesis process, causing severe degradation of the image quality. In order to reduce the noise during the HDR synthesis process, a de-noising scheme based on half-quadratic regularization is proposed for the synthesis of HDR images in this paper. By taking into consideration of two unique HDR image features, the proposed scheme effectively removes the noise, while the edges still being well preserved in the synthesized HDR images.
Local Inverse Tone Mapping for Scalable High Dynamic Range Image Coding

Tone mapping operators (TMOs) and inverse TMOs (iTMOs) are important for scalable coding of high dynamic range (HDR) images. Because of the high nonlinearity of local TMOs, it is very difficult to estimate the iTMO accurately for a local TMO. In this letter, we present a two-layer local iTMO estimation algorithm using an edge-preserving decomposition technique. The low dynamic range (LDR) image is first linearized and then decomposed into a base layer and a detail layer via a fast edge-preserving decomposition method. The base layer of the HDR image is generated by subtracting the LDR detail layer from the HDR image. An iTMO function is finally estimated by solving a novel quadratic optimization problem formulated on the pair of base layers rather than the pair of HDR and LDR images as in existing methods. Experimental results show that the proposed two-layer iTMO can recover the HDR accurately so that it is possible to use these local TMOs in scalable HDR image coding schemes.