Quality Enhancement Algorithm Research Articles

Video thumbnail extraction for HEVC

This paper proposes a thumbnail quality enhancement algorithm that uses a predefined weight table. Conventional thumbnail extraction algorithms in high efficiency video coding use a simple downsampling method to produce thumbnail images with low complexity, resulting in thumbnail quality deterioration. The proposed algorithm estimates the original average values of each thumbnail pixel using a weighted average value of several pixels, based on intra-mode direction. The proposed method improves the visual quality of thumbnail images while maintaining low complexity.

A new two‐microphone Gauss‐Seidel pseudo affine projection algorithm for speech quality enhancement

SummaryThis study addresses the problem of speech quality enhancement by adaptive and nonadaptive filtering algorithms. The well‐known two‐microphone forward blind source separation (TM‐FBSS) structure has been largely studied in the literature. Several two‐microphone algorithms combined with TM‐FBSS have been recently proposed. In this study, we propose 2 contributions: In the first, a new two‐microphone Gauss‐Seidel pseudo affine projection (TM‐GSPAP) algorithm is combined with TM‐FBSS. In the second, we propose to use the new TM‐GSPAP algorithm in speech enhancement. Furthermore, we show the efficiency of the proposed TM‐GSPAP algorithm in speech enhancement when highly noisy observations are available. To validate the good performances of our algorithm, we have evaluated the adaptive filtering properties in computational complexity and convergence speed performance by system mismatch criteria. A fair comparison with adaptive and nonadaptive noise reduction algorithms are also presented. The adaptive algorithms are the well‐known two‐microphone normalized least mean square algorithm, and the recently published two‐microphone pseudo affine projection algorithm. The nonadaptive algorithms are the one‐microphone spectral subtraction and the two‐microphone Wiener filter algorithm. We evalute the quality of the output speech signal in each algorithm by several objective and subjective criteria as the segmental signal‐to‐noise ratio, cepstral distance, perceptual evaluation of speech quality, and the mean opinion score. Finally, we validate the superior performances of the proposed algorithm with physically measured signals.

A New Control Algorithm for Power Quality Improvement in a Stand-alone Synchronous Reluctance Generator with Energy Storage

This article presents an adaptive control algorithm for power quality enhancement of a synchronous reluctance generator based stand-alone generator system with a battery energy storage system by employing the compensation capabilities of a voltage source converter. The proposed synchronous reluctance generator system is implemented using a 3.75-kW synchronous reluctance generator, a voltage source converter with a battery support, and a digital signal processor. The control algorithm is used for estimation of reference currents keeping in view the limited rating of the voltage source converter. A modified leaky least mean square algorithm using a variable-step–variable-weight factor is proposed for the control. The variable-step–variable-weight least mean square algorithm decomposes the load currents, extracts its real positive-sequence component to track the unit vectors by varying the rate of convergence of the algorithm, and accordingly tunes the weights, thus enabling selective compensation. The proposed control algorithm offers satisfactory harmonics mitigation, compensation of reactive power demand, and load balancing of a stand-alone synchronous reluctance generator system under linear/non-linear and dynamic loads.

A new regularized forward blind source separation algorithm for automatic speech quality enhancement

Abstract This paper addresses the problem of speech enhancement and acoustic noise reduction by adaptive filtering algorithms in a moving car through blind source separation (BSS) structures. In this paper we propose a new regularized forward blind source separation (RFBSS) algorithm that does not need voice activity detection (VAD) systems, and allows getting efficient speech enhancement performances with low complexity. The proposed RFBSS algorithm is compared with recent and classical speech enhancement algorithms in different noisy conditions. This comparison is evaluated in terms of Cepstral distance (CD), the system mismatch (SM) and the Segmental signal-to-noise ratio (SegSNR) criteria. The obtained results show the efficiency of the proposed algorithm and its superiority in comparison with competitive algorithms in speech enhancement applications.

An efficient frequency-domain adaptive forward BSS algorithm for acoustic noise reduction and speech quality enhancement

In this paper, we consider the speech enhancement and acoustic noise reduction problem in a moving car through a blind source separation scheme employing two loosely spaced microphones. We propose a new efficient frequency domain-symmetric adaptive decorrelation (FD-SAD) algorithm that removes punctual noise components from noisy speech signals. The FD-SAD algorithm is combined with the forward blind source separation FBSS structure to enhance the performances of its time-domain symmetric adaptive decorelating (TD-SAD) version. The proposed algorithm has a good tracking behaviour and fast convergence speed even in very noisy conditions with loosely spaced microphones. Intensive experiments have been done on the newly proposed algorithm in terms of the Segmental Signal-to-Noise-Ratio (SegSNR), the System Mismatch (SM), the Segmental Mean Square Error (SegMSE), and the Cepstral Distance (CD) criteria. The comparison results with the state-of-the-art algorithms have highlighted the excellent performance of the proposed algorithm, and have shown its ability to completely remove the correlated noise components from speech signal even in very noisy conditions when controlled by a voice activity detector.

Photo quality enhancement by relocating subjects

Photo quality enhancement by photographic evaluation is a challenging problem in photography. In this paper, a new photo quality enhancement algorithm for photographic recomposition based on subjec...

Improved subband-forward algorithm for acoustic noise reduction and speech quality enhancement

This paper addresses the problem of speech enhancement and acoustic noise reduction by adaptive filtering algorithms. Recently, we have proposed a new Forward blind source separation algorithm that enhances very noisy speech signals with a subband approach. In this paper, we propose a new variable subband step-sizes algorithm that allows improving the previous algorithm behaviour when the number of subband is selected high. This new proposed algorithm is based on recursive formulas to compute the new variable step-sizes of the cross-coupling filters by using the decorrelation criterion between the estimated sub-signals at each subband output. This new algorithm has shown an important improvement in the steady state and the mean square error values. Along this paper, we present the obtained simulation results by the proposed algorithm that confirm its superiority in comparison with its original version that employs fixed step-sizes of the cross-coupling adaptive filters and with another fullband algorithm.

High-performance depth map coding for 3D-AVC

Achieving high-performance coding for a depth map is one of the most important challenges in 3D video coding. In this paper, a quality enhancement method is proposed to accomplish better coding efficiency. A new technique separating contour and flat regions is designed, and a contour-aware quality enhancement algorithm is presented to improve depth map quality. We also propose a fast mode decision process to reduce computational complexity. The proposed fast algorithm uses similarity between texture video and depth map coding. The encoding process for a depth map is terminated early by using coded information from a texture video. Experimental results show that the quality of the depth map is improved by 0.11–0.59 dB, which translates into a bit rate saving of 2.19–8.19 %. The proposed fast algorithm saves encoding time, on average, by 36.4 %.

A pixel-based outlier-free motion estimation algorithm for scalable video quality enhancement

Scalable video quality enhancement refers to the process of enhancing low quality frames using high quality ones in scalable video bitstreams with time-varying qualities. A key problem in the enhancement is how to search for correspondence between high quality and low quality frames. Previous algorithms usually use block-based motion estimation to search for correspondences. Such an approach can hardly estimate scale and rotation transforms and always introduces outliers to the motion estimation results. In this paper, we propose a pixel-based outlier-free motion estimation algorithm to solve this problem. In our algorithm, the motion vector for each pixel is calculated with respect to estimate translation, scale, and rotation transforms. The motion relationships between neighboring pixels are considered via the Markov random field model to improve the motion estimation accuracy. Outliers are detected and avoided by taking both blocking effects and matching percentage in scale-invariant feature transform field into consideration. Experiments are conducted in two scenarios that exhibit spatial scalability and quality scalability, respectively. Experimental results demonstrate that, in comparison with previous algorithms, the proposed algorithm achieves better correspondence and avoids the simultaneous introduction of outliers, especially for videos with scale and rotation transforms.

UHD TV 영상신호처리를 위한 프로그래머블 멀티미디어 플랫폼

2 3458K(7680x4320) UHD(Ultra High Definition) TV346789: ; !# ?)*+:>@AB CDEF. 8K :BG60 HIJ DK L45MNOPQROSTU;V6WXUYZ[\](^ F. C _`a345bS6cd $%efgh0i, efghj[k[hl[ m[n: ok[hpg0iqrhost: Duv(wxK 0N]yF. -0Nz >4(Reconfigurable Processor) K{6 C|)*+}F~ 789M€:0‚ƒ„J , UHD †‡q'g)H[pˆ‰N3M€6Šk[‹1J UŒ[wO Ž:M„F. AbstractThis paper introduces the world’s first programmable video-processing platform for the enhancement of the video quality of the 8K(7680x4320) UHD(Ultra High Definition) TV operating up to 60 frames per second. In order to support required computing capacity and memory bandwidth, the proposed platform implemented several key features such as symmetric multi-cluster architecture for parallel data processing, a ring-data path between the clusters for data pipelining and hardware accelerators for computing filter operations. The proposed platform based on RP(Reconfigurable Processor) processes video quality enhancement algorithms and handles effectively new UHD broadcasting standards and display panels.Keyword : programmable multimedia platform, reconfigurable processor, UHD TV

A computational photography algorithm for quality enhancement of single lens imaging deblurring

Modern single lens reflex lenses typically consist of up to two dozen individual optical elements, the complexity of which is necessary to compensate for geometric and chromatic aberrations. This paper adopts one single lens to capture images instead of complex lenses, and computational photography technique is employed to remove corresponding imaging artifacts. We initially estimate the space-variant point spread function of the single lens by combining l1/l2 image and sparse kernel priors. A fast non-blind deconvolution method with hyper-Laplacian prior is then performed to recover clear image. Experimental results show that the proposed method is at par with state-of-the-art non-blind deconvolution approaches, especially with regards its speed that is much faster than that of existing methods.

Optimum placement of active power conditioner in distribution systems using improved discrete firefly algorithm for power quality enhancement

This paper presents an improved solution for optimal placement and sizing of active power conditioner (APC) to enhance power quality in distribution systems using the improved discrete firefly algorithm (IDFA). A multi-objective optimization problem is formulated to improve voltage profile, minimize voltage total harmonic distortion and minimize total investment cost. The performance of the proposed algorithm is validated on the IEEE 16- and 69-bus test systems using the Matlab software. The obtained results are compared with the conventional discrete firefly algorithm, genetic algorithm and discrete particle swarm optimization. The comparison of results showed that the proposed IDFA is the most effective method among others in determining optimum location and size of APC in distribution systems.

Space charge dynamics investigation based on Kerr electro-optic measurements and processing of CCD images

The Kerr electro-optic technique is used to investigate electric field and space charge effects using large Kerr constant propylene carbonate as the dielectric liquid with Kerr constant B≈1.22×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-12</sup> m/V <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . However, improved accuracy of this technique to measure space charge distributions remains an important goal. This paper describes inversion algorithm research on obtaining accurate space charge distributions from Kerr measurements. The original charge-coupled device (CCD) image of light intensity was converted into grayscale values for improved calculation. The grayscale CCD image was transformed into the frequency domain through a two-dimensional Fourier transformation. Butterworth filtering techniques were employed for edge enhancement algorithms. The most important parameter for calculation of space charge distributions are the integer fringe numbers n in the sequence of light and dark fringes measured by the CCD camera. Comparison of the improved algorithm and traditional methods for calculating electric field and space charge distributions between a pair of stainless steel parallel plate electrodes was investigated. The space charge dynamics were also calculated after processing the CCD images with some improvements. The results showed the electric field was essentially uniform at early times of pulsed high voltages. This uniformity indicated the absence of space charge during the early transient interval, while a bipolar charge injection was found in the central region between electrodes at later times. For longer times the electric field and space charge distributions slowly became uniform again. Grayscale processing and Butterworth filtering played an important role in the improvement of the algorithm for better image quality and edge enhancement.

Android 플랫폼에서 구현 기술에 따른 화질 개선 연산 성능 비교

As mobiles devices with high-spec camera built in are used widely, the visual quality enhancement of the high-resolution images turns out to be one of the key capabilities of the mobile devices. Due to the limited computational resources of the mobile devices and the size of the high-resolution images, we should choose an image processing algorithm not too complex and use an efficient implementation technology. One of the simple and widely used image quality enhancement algorithms is contrast stretching. Java libraries running on a virtual machine, JNI (Java Native Interface) based native C/C++, and NEONTM SIMD (Single Instruction Multiple Data) are common implementation technologies in the case of Android smartphones. Using these three implementation technologies, we have implemented two image contrast stretching algorithms - linear and equalized, and compared the computation times. The native C/C++ and the NEONTM SIMD outperformed the native C/C++ implementation by 56-78 and 50-76 time faster respectively.

A two-step approach to see-through bad weather for surveillance video quality enhancement

Adverse weather conditions such as snow, fog or heavy rain greatly reduce the visual quality of outdoor surveillance videos. Video quality enhancement can improve the visual quality of surveillance videos providing clearer images with more details to better meet human perception needs and also improve video analytics performance. Existing work in this area mainly focuses on the quality enhancement for high-resolution videos or still images, but few algorithms are developed for enhancing surveillance videos, which normally have low resolution, high noises and compression artifacts. In addition, for snow or rain conditions, the image quality of near-field view is degraded by the obscuration of apparent snowflakes or raindrops, while the quality of far-field view is degraded by the obscuration of fog-like snowflakes or raindrops. Very few video quality enhancement algorithms have been developed to handle both problems. In this paper, we propose a novel video quality enhancement algorithm for see-through snow, fog or heavy rain. Our algorithm not only improves human visual perception experiences for video surveillance, but also reveal more video contents for better video content analyses. The proposed algorithm handles both near-field and far-field snow/rain effects by proposed a two-step approach: (1) the near-field enhancement algorithm identifies obscuration pixels by snow or rain in the near-field view and removes these pixels as snowflakes or raindrops; different from state-of-the-art methods, our proposed algorithm in this step can detect snowflakes on foreground objects or background, and apply different methods to fill in the removed regions. (2) The far-field enhancement algorithm restores the image’s contrast information not only to reveal more details in the far-field view, but also to enhance the overall image’s quality; in this step, the proposed algorithm adaptively enhances the global and local contrast, which is inspired on the human visual system, and accounts for the perceptual sensitivity to noises, compression artifacts, and the texture of image content. From our extensive testing, the proposed approach significantly improves the visual quality of surveillance videos by removing snow/fog/rain effects.

Dynamic hybrid automatic repeat request (DHARQ) for WiMAX – Mobile multihop relay using adaptive power control

Wireless multihop network is currently attracting much attention as a new wireless broadband access technology due to numerous benefits. This work proposes a power control scheme for WiMAX multihop relay system. In contrast to existing power control and optimization approaches, our proposed method uses an adaptive Channel Quality Measurement for a relay station to reduce interferences to other mobile station (MS) or relay station (RS) within the same cell and hence increase the number of hops per link and consequently maximize the spatial reuse. The proposed power control is applied to a new dynamic HARQ algorithm for adaptive channel quality enhancement. Simulation results have indicated that the proposed approach achieves superior BER/PER performance enhancement in comparison to previous related works.

Improving verification accuracy by synthesis of locally enhanced biometric images and deformable model

In this paper, we propose a 2-stage preprocessing framework which consists of image enhancement and deformation techniques to increase the verification performance of image-based biometric systems. In the preprocessing framework, first the quality of biometric image is enhanced and then a deformation model is applied to minimize the variation between the two images to be matched. The proposed SVM image quality enhancement algorithm selects good quality regions from different globally enhanced images and combines them to generate a single high-quality feature-rich image. The proposed deformation algorithm is based on phase congruency information and locally minimizes the variations between two images while retaining the features required for recognition. The proposed algorithms are validated using face and iris biometrics as the two case studies. For performance evaluation, different face and iris recognition algorithms are chosen and the verification accuracy is computed using non-homogenous face and iris databases. Experimental results show that the performance of face and iris recognition algorithms are significantly improved when the input images are preprocessed using the proposed enhancement and deformation algorithms.

Generalized Gaussian Decompositions for SAR Enhancement Using Analysis-by-Synthesis

Britton, D. F., and Smith, M. J. T., Generalized Gaussian Decompositions for SAR Enhancement Using Analysis-by-Synthesis, Digital Signal Processing 12 (2002) 284–294 Quality enhancement algorithms for synthetic aperture radar (SAR) images offer the potential to increase the accuracy of analysis and threat assessment. This paper presents a new SAR image enhancement method for that purpose. The method is built around a Gaussian representation of the image using analysis-by-synthesis as the engine for the approximation. Its sequential structure and synthesis property enables object boundaries and speckle characteristics to be decoupled and modified to enhance the quality. Evaluations demonstrate that the algorithm helps improve the performance of automatic target recognition systems as well as enhance subjective appearance.

Iteratively Clustered Interpolation (ICI) Algorithm for Geometrical Interpolation of an Irregularly Spaced Multidimensional Color Space

A printer inverse map is usually represented as a multivariable lookup table, associating points in the printer's output color space with points in the printer's input color space. This lookup table is an essential component in many print quality enhancement algorithms. It is often desirable to have a printer inverse table with input nodes regularly spaced on a sequential plane. Thus, the computation of this lookup table requires the interpolation of irregularly sampled multidimensional data, coming from experiments used to determine the printer forward map. Existing computational techniques do not provide an accurate printer inverse map from irregularly sampled data. In this paper we introduce a new Iteratively Clustered Interpolation (ICI) algorithm to compute an accurate inverse table from irregularly sampled color data. This algorithm is based on a gradient optimization method with initial points generated through a novel iterative technique. Experimental results are included to show the effectiveness of this algorithm in comparison with other techniques.