nils-herrmann/clean_scirepeval huggingface dataset:
A fast two-stage OMP algorithm for coding stereo image residuals

Over-complete signal decomposition has been shown to be an efficient technique for coding disparity compensated residual images in stereo image pairs. This paper presents a residual image coding scheme based on a recently proposed MP-based coding scheme called SOSU. The proposed scheme decomposes an orthogonal matching pursuit process into two stages. In different stages, dictionaries of different nature are used. Simulation results show that the proposed scheme can significantly reduce the computation effort while maintaining a similar rate-distortion performance as compared with SOSU.
Image enlargement using fractal

In fractal coding technique, an image is encoded by making use of its self-similarity property. The image can be reconstructed with some well-defined contractive mappings based on this property and hence, in theory, the reconstructed image can be of any desirable size by using an initial image of appropriate size during the decoding process. However, in practice, the enlarged image is always degraded due to the sub-optimal contractive mappings used. In this paper, a fractal-based image enlargement technique is proposed to reduce this problem. This technique can preserve the details in edge regions while maintaining the smoothness in flat regions, which is superior to conventional image enlargement techniques such as bilinear interpolation and cubic convolution.
Restoring halftoned color-quantized images with simulated annealing

Restoration of color-quantized images is rarely addressed in the literature, especially when the images are color-quantized with halftoning. Direct applications of existing restoration techniques are generally inadequate to deal with this problem. A restoration algorithm based on simulated annealing is proposed to solve the problem. This algorithm makes a good use of the available color palette and the mechanism of a halftoning process to derive useful a priori information for restoration. It is shown to be able to provide a good restoration result.
A practical real-time post-processing technique for block effect elimination

In this paper, a non-iterative post-processing method is proposed to restore the images encoded with block-based compression standards such as JPEG. This method classifies small local boundary regions according to their intensity distribution and then select appropriate linear predictors to estimate the corresponding boundary pixels in the regions. This approach is easy to implement and we found in our simulations that its restoration performance was very respectable compared with the reported post-processing methods.
A low-complexity multiscale error diffusion algorithm for digital halftoning

Multiscale error diffusion (MED) digital halftoning technique outperforms classical conventional error diffusion techniques as it can produce a directional-hysteresis-free bi-level image. However, extremely large computation effort is required for its implementation. In this paper, a fast MED-based digital halftoning technique is proposed to produce a halftone image without directional hysteresis at a significantly reduced computational cost. The amount of reduction is monotonic increasing with the image size. For an image of size 512/spl times/512, the proposed algorithm can save 40% of arithmetic operations as compared with MED. Moreover, since it supports parallel processing, processing time can further be squeezed.
Preserving image features in digital halftoning with a multiscale error diffusion technique

Multiscale error diffusion is superior to conventional error diffusion methods in digital halftoning as it can completely eliminate directional hysteresis. However, there is a bias to favor a particular type of dot in the course of the halftoning process. A new multiscale error diffusion method is proposed to improve the diffusion performance by reducing the aforementioned bias. The proposed method can also eliminate the boundary effect found in conventional multiscale error diffusion methods and preserve the local features of the input image in the output. This is critical to the quality when the resolution of the output is limited by the physical constraints of the display unit.
Reducing the Complexity of Multiscale Error Diffusion

Multiscale error diffusion (MED) is superior to conventional error diffusion algorithms as it can eliminate directional hysteresis completely. However, the complexity of this frame-oriented process is much higher and makes it not suitable for real-time applications. In this paper, a fast MED algorithm is proposed. The complexity of this algorithm is remarkably reduced as compared with conventional MED algorithms. It also supports parallel processing
Restoration of Halftoned Color-Quantized Images using Linear Estimator

Restoration of color-quantized images in which error diffusion is involved is rarely addressed in the literature. Conventional restoration algorithms were generally proposed for handling other noise models and hence they are not effective in restoring color-quantized images. In this paper, we tackle this problem by making use of the best linear estimation. It is shown by the simulation results that the algorithm can improve the quality of color-quantized images to a certain extent
An adaptive constrained least square approach for removing blocking effect

This paper presents a new adaptive objective function based on the regularized iterative block reduction technique for low-bit rate transform coded images. Also, a better initial estimate for the regularization approach is presented. Two types of prior knowledge are used: the first type bounds the maximum tolerable error (roughness), and the second type restricts the high-frequency content (smoothness) of the restorated images. Computer simulations showed that the new adaptive objective function with the proposed initial estimate performed better on both subjective and objective measures than did a previously proposed objective function.
An efficient weight optimization algorithm for image representation using nonorthogonal basis vectors

Though image-coding techniques that employ subsets of nonorthogonal basis images chosen from two or more transform domains have been shown consistently to yield higher image quality than those based on one transform for a fixed compression ratio, they have not been widely employed due to their very high computational complicity of existing realization approaches. This paper presents a new realization approach for mixed-transform image representation. Computational complexity can be greatly reduced compared with existing approaches.
Removing harmonic distortion in tiled screens

When producing halftones with the screening technique, tiling is generally used to construct a screen of appropriate size with screens of small fixed size. Regular tiling and random tiling are two common tiling schemes used nowadays. The former scheme produces periodic screens which introduce harmonic distortion to the screening outputs while the latter may introduce blocking artifacts as the possible connections among adjacent blocks are too many for a training algorithm to train the small screens that are used for tiling. This paper addresses this issue and proposes a new tiling scheme that allows one to train small screens to construct large screens seamlessly. Simulation results show that a screen constructed with the proposed tiling screen bears blue noise characteristics, contains no blocking artifacts and little harmonic distortion.
Regularised restoration of vector quantisation compressed images

The authors study the application of image restoration technology in improving the coding performance of a vector quantisation (VQ) image compression codec. Restoration of VQ-compressed images is rarely addressed in the literature, and direct applications of existing restoration techniques are generally inadequate to deal with this problem. A restoration algorithm is proposed, specific to VQ-compressed images, that makes good use of the codebook to derive useful a priori information for restoration. The proposed restoration algorithm is shown to be capable of improving the quality of a VQ-compressed image to a much greater extent, compared with other existing restoration approaches. As no extra information, other than the codebook, is required to carry out the restoration with the proposed algorithm, no transmission overhead is necessary and hence, it can be fully compatible with any VQ codec when used to improve coding performance.
A multiscale color error diffusion algorithm for color quantization

This paper presents a new multiscale vector error diffusion algorithm for color quantization. This iterative algorithm selects a pixel, color-quantizes it and then diffuses the quantization error with a non-causal filter at each iteration until all pixels are color-quantized. By doing so, directional hysteresis is completely eliminated and color impulses can be reduced to a certain extent. Simulation results show that it provides better outputs in terms of S-CIELAB color difference metric as compared with conventional approaches. The subjective quality of the output is also improved.
A Low-Complexity Joint Color Demosaicking and Zooming Algorithm for Digital Camera

This paper presents a low complexity joint color demosaicking and digital zooming algorithm for single-sensor digital cameras. The proposed algorithm directly extracts edge information from raw sensor data for interpolation in both demosaicking and zooming to preserve edge features in its output. This allows the extracted information to be exploited consistently in both stages and also efficiently, as no separate extraction process is required in different stages. The proposed algorithm can produce a zoomed full-color image as well as a zoomed Bayer color filter array image with outstanding performance as compared with conventional approaches which generally combine separate color demosaicking and digital zooming schemes.
An iterative algorithm for restoring color-quantized images

This paper studies the restoration of color-quantized images. Restoration of color-quantized images is rarely addressed in the literature, and direct applications of existing restoration techniques are generally inadequate to deal with this problem. We propose a POCS-based restoration algorithm specific to color-quantized images, which makes a good use of the available color palette to derive useful a priori information for restoration. The proposed restoration algorithm is shown to be capable of improving the quality of a color-quantized image to a certain extent.
A new approach for restoring block-transform coded images with estimation of correlation matrices

This paper presents a new restoration approach to reduce coding artifacts in block-transform image coding. Different from conventional restoration techniques, the proposed one is non-iterative and requires a low computational cost, yet can reconstruct objectively and subjectively better images. This good performance is achieved because of the following advantages the proposed approach has: (i) efficient incorporation of the solution bound into restoration; and (ii) effective exploitation of local image properties and statistical knowledge about the quantizers used.
A new convolution structure for the realisation of the discrete cosine transform

A formulation for converting a length-N, where N=2/sup m/ and m is an integer, discrete cosine transform into two length-N/2 correlations is presented. This formulation enables the authors to realize the discrete cosine transform with a reduced number of operations compared to conventional approaches, and it also results in extremely regular structure, which is most suitable for a realization using distributed arithmetic.<<ETX>>
A Lossless Compression Scheme for Bayer Color Filter Array Images

In most digital cameras, Bayer color filter array (CFA) images are captured and demosaicing is generally carried out before compression. Recently, it was found that compression-first schemes outperform the conventional demosaicing-first schemes in terms of output image quality. An efficient prediction-based lossless compression scheme for Bayer CFA images is proposed in this paper. It exploits a context matching technique to rank the neighboring pixels when predicting a pixel, an adaptive color difference estimation scheme to remove the color spectral redundancy when handling red and blue samples, and an adaptive codeword generation technique to adjust the divisor of Rice code for encoding the prediction residues. Simulation results show that the proposed compression scheme can achieve a better compression performance than conventional lossless CFA image coding schemes.
Shaping the Spatial and Temporal Noise Characteristics of Driving Signals for Driving AMOLED Display

In this paper, a digital driving technique for generating binary driving signals to display a digital video on an active-matrix organic light-emitting diode (AMOLED) panel is proposed. The ideal spatial and temporal noise characteristics of the driving signal for an AMOLED panel to display high-quality video are first suggested. Based on the suggested characteristics, a digital driving technique is proposed to generate the driving signals for an AMOLED panel. Simulation results show that the proposed driving technique can generate driving signals having the desired spatial and temporal noise characteristics and, accordingly, allows an AMOLED panel to display video of better quality than other conventional driving techniques in terms of various measures.
Optimized multilevel fringe patterns for real-time 3D shape measurement with defocused projector

Binary defocusing method is an efficient technique for 3D measurement. It allows real-time measurement by replacing conventional 8-bit fringe patterns with binary patterns. However, there is still room for improving the measurement accuracy of binary defocusing method. This paper presents a novel idea of projecting binary patterns through different color channels of a projector to increase the intensity levels of a fringe pattern without sacrificing the advantages of binary defocusing method. An algorithm is also proposed to optimize fringe patterns for the application. Both simulation and experimental results show that our method can improve the measurement accuracy substantially.
Efficient blind image restoration using discrete periodic Radon transform

Restoring an image from its convolution with an unknown blur function is a well-known ill-posed problem in image processing. Many approaches have been proposed to solve the problem and they have shown to have good performance in identifying the blur function and restoring the original image. However, in actual implementation, various problems incurred due to the large data size and long computational time of these approaches are undesirable even with the current computing machines. In this paper, an efficient algorithm is proposed for blind image restoration based on the discrete periodic Radon transform (DPRT). With DPRT, the original two-dimensional blind image restoration problem is converted into one-dimensional ones, which greatly reduces the memory size and computational time required. Experimental results show that the resulting approach is faster in almost an order of magnitude as compared with the traditional approach, while the quality of the restored image is similar.
A practical postprocessing technique for real-time block-based coding system

A noniterative postprocessing method is proposed to restore the images encoded with block-based compression standards such as Joint Photographic Experts Group (JPEG). This method classifies small local boundary regions according to their intensity distribution and then selects appropriate linear predictors to estimate the corresponding boundary pixels in the regions. This approach is easy to implement and we found in our simulations that its restoration performance was very respectable compared with the reported postprocessing methods.
A robust model generation technique for model-based coding

In conventional model-based coding schemes, predefined static models are generally used. These models cannot adapt to new situations and hence they have to be very specific and cannot be generated from a single generic model even though they are very similar. In this paper, we present a model generation technique that can gradually build a model and dynamically modify it according to new video frames scanned. The proposed technique is robust to the object's orientation in the view and can be efficiently implemented with parallel processing technique. As a result, the proposed technique is more attractive to the practical use of model-based coding techniques in real applications.
Efficient implementation of discrete cosine transform using recursive filter structure

We generalize a formulation for converting a length-2/sup n/ discrete cosine transform into n groups of equations, then apply a novel technique for its implementation. The sizes of the groups are 2/sup n-1/, 2/sup n-2/, ...2/sup 0/ respectively, while their structures are extremely regular. The realization can then be converted into recursive filter form, which is particularly simple for practical implementation.
An improved algorithm for removing impulse noise based on long-range correlation in an image

An algorithm for removing impulse noise is proposed. The algorithm not only uses the information of neighboring pixels in a local region, but also uses the long-range correlation within a natural image. In the proposed algorithm, a search criterion based on the weighted transformed contents of regions is used to look for a region which is highly correlated to the region of interest and then the center of that region is selected to replace the corrupted pixel. The method is found to be very effective in removing impulse noise from corrupted images, both in terms of the objective distortion measure and subjective visual assessment.
Subband adaptive regularization method for removing blocking effect

This paper presents two new approaches to removing the blocking effect in low-bit rate transform coded images by using a subband decomposition/reconstruction technique. They are designed to act as a supplementary post-processing step of the JPEG standard. Both approaches make use of the noise characteristics of each subband to bound the maximum tolerable error and the smoothness of the restored images in restoring the subband images by regularization. In one method the spatial activity of the restored images is also used to tighten the bounds. Computer simulations show that the new adaptive objective functions could achieve a better restoration performance in terms of both subjective and objective measures than other conventional objective functions.
Edge preserving multiscale error diffusion algorithm for green noise digital halftoning

Multiscale error diffusion (MED) is superior to conventional error diffusion algorithm as it can eliminate directional hysteresis completely and possesses good blue noise characteristics. However, due to its filter design, it is not suitable for printing processes which suffer instable dot generation and large dot gain. This paper presents a feature preserving multiscale error diffusion algorithm for green noise digital halftoning. To cope with the edge of the image, the selected diffusion filter is modified according to the edge orientation. Spatial statistics analysis and simulation results show that the proposed algorithm does not only provide outputs of green noise characteristics, but preserve edge details and eliminate pattern artifacts and directional artifacts as well.
Embedding halftones of different resolutions in a full-scale halftone

To efficiently render halftone images for various printers and displays that support different resolutions, it is desirable that all halftoning results can be produced at a time, and all of them can be embedded in a single full-scale halftone image such that a simple down-sampling process can extract images of suitable resolutions from it if necessary. This letter presents a framework for achieving this objective with multiscale error diffusion. A multi-resolution halftoning algorithm is proposed based on this framework. Simulation results show that the proposed algorithm can provide good image quality at different resolutions.
New formulation of fast discrete Hartley transform with the minimum number of multiplications

A simple algorithm is proposed to realize a one-dimensional discrete Hartley transform (DHT) with sequence lengths equal to 2/sup m/. This algorithm achieves the same multiplicative complexity as Malvar's algorithm (1987, 1988) which requires the least number of multiplications reported in the literature. However, the approach gives the advantage of requiring a smaller number of additions compared with the number required in Malvar's algorithm.<<ETX>>
The neural network modelled POCS method for removing blocking effect

This paper proposes a new method for real-time realization on the blocking effect elimination. This is achieved by training a feed-forward single-layer neural network (FFSLN) to restore block boundaries of JPEG encoded images. The reconstructed image of the iterative projection onto convex sets (POCS) method instead of the original image is chosen as the target output in this proposed method. Computer simulation result demonstrates the superiority of the new method as compared with the original POCS iterative recovery method.
Adoption of business continuity planning processes in IT service management

For any fault of the same severity level, traditional fault discovery and notification tools provide equal weighting from business points of view. To improve the fault correlation from business perspectives, we proposed a framework to automate network and system alerts with respect to its business service impact for proactive notification to IT operations management. This paper outlines the value of business continuity planning (BCP) during the course of service impact analysis, placing particular emphasis on the business perspective in the processes of IT service management. The framework explicitly employs BCP relevant processes in order to identify the relationships between business services and IT resources A practical case in IT operations to illustrate the concept was then conducted.
An edge-directed demosaicing algorithm based on integrated gradient

In this paper, an efficient edge-directed demosaicing algorithm for Bayer images is presented. A new edge-sensing measure called integrated gradient (IG) is exploited to extract gradient information in both color intensity and color difference domains simultaneously for the interpolations. This measure supports full resolution and allows one to interpolate the missing samples along an appropriate direction. By sharing it in different stages, it guarantees consistency of the interpolation direction in different channels and saves the effort required to repeatedly extracting gradient information from intermediate interpolation results. An IG-based green plane enhancement is also proposed to further improve the method's efficiency. Simulation results confirmed that the proposed demosaicing algorithm outperforms most up-to-date demosaicing algorithms in terms of both quality and complexity.