nils-herrmann/clean_scirepeval huggingface dataset:
Integer fast lapped orthogonal transform based on direct-lifting of dcts for lossless-to-lossy image coding

Integer lapped orthogonal transforms (LOTs) are vital technologies for the unification of lossless and lossy image coding, called lossless-to-lossy image coding. In this paper, we present an efficient realization of integer fast LOT (FLOT) based on direct-lifting of discrete cosine transforms (DCTs) which are type-II, III and IV. Although the conventional integer FLOTs suffer from degradation of coding performance due to much rounding error generated by cascading lifting structures, this paper presents a realization of a simpler, faster and more efficient transform with only some adders, 1-bit shifters and direct use of DCTs for lifting coefficients. As result, the proposed method is validated in lossless-to-lossy image coding.
A Design of Dual-Tree Complex Wavelet Transform Based on Least Squares Method

In this paper, a novel design of dual-tree complex wavelet transform based on least squares method is proposed. An effective design method based on allpass filter with FIR has proposed by Selesnick. However, this method holds two problems. First, optimal frequency characteristic cannot be realized due to the restriction of design parameters. Second, approximation of the half sample delay condition is restricted on low frequency. The proposed method can achieve the high design degrees of freedom by using least squares method. It is shown that the method can design more effective dual-tree complex wavelet transform than conventional one, in terms of sharpness of frequency characteristic and accuracy of half sample delay condition, directionality and shift-invariance, by simulations. In the end of this paper, the performance of DTCWT designed by the proposed method for practical application, image denoising, is demonstrated. The proposed method outperforms the conventional method.
Hierarchical Stereo Matching Via Color Segmentation

This paper presents a new segment-based stereo matching algorithm using a coarse-to-fine multiresolution strategy. In general, the multiresolution scheme was employed in a direct descending optimization to avoid matching in the local minimal. However, it is not effective in homogeneously textured regions and disparity discontinuous boundaries. We implement a novel hierarchical segment-based matching scheme to produce accurate disparity maps, which resolves the above mentioned challenging problems. We utilize the hierarchical color segmentation that is classified in each resolution level to guide the matching process gradually. The principal feature of our scheme is to combine the local and the global optimization in multiresolution stages. To validate the proposed algorithm, we show the experimental results on the new Middlebury database sets
Super-resolutions based on shock filter and non local means with BM3D for congruity

In this paper, we propose two kind of image superresolution methods based on the shock filter and non local means(NLM). One is a method using shock filter to enhance the high frequency components. Another is a method using NLM based on self similarity of images. Compared with interpolation, super-resolution should produce high resolution images by correctly generating their missing high frequency components. The shock filter based method only applies the shock filter to the high frequency components of an enlarged image by the linear interpolation method. Since the proposed method effectively enhances the sharpness of edges and avoids the over enhancement of texture and smooth regions, the enlarged image is natural and the computational complexity is very low. The NLM based method achieves a high resolution image by using self similarity. It is possible to reduce computational complexity and get good quality of the image by the similarity between the low and high resolution images. In order to improve the quality further, we utilize BM3D which is used in denoising for the super-resolution based on image congruity. In simulations, the proposed method objectively and perceptually shows better results than the conventional method.
Cosine-modulated two-dimensional time-varying filter banks

Two-dimensional (2-D) filter banks are widely used for analysis and synthesis systems applied to subband coding of image. Time-varying filter banks that vary the structure of them appropriately for a local property of the signal have been studied for image data compression. In time-varying filter banks, each different part of the signal is processed with different filter coefficients or a different number of channels (a different sampling matrix). Those signals have to be perfectly reconstructed even across the transition of the filter banks. We consider time-varying systems of cosine-modulated 2-D filter banks for arbitrary sampling lattices. We show perfect reconstruction (PR) conditions for such time-varying filter banks that vary the filter coefficients or a sampling matrix. Some applications are presented to show the effectiveness of this method.
All-in-focus Photo image Creation by Wavelet Transform

In this paper, we describe a deblurring method using Image-Fusion of multiple images taken with different object-distances. Our method uses the wavelet transform for the fusion, but we create new wavelet coefficients by mixing each pixel value by using "reference image usage rate (IUR)". And we present simple and effective algorithms "Fusion rule for the lowest frequency subband" "Noise reduction algorithm" "Blur reduction algorithm" that use this IUR.  When we take a photo, we adjust the object-distance (focus position) manually or automatically to take the clear image of the photographic subject. In other words, we put the subject into the zone of focus that is called depth-of-field. However, in the case of the short object distance, the zone becomes too narrow to cover the whole region of the subject(s) and the image of such regions become unclear. But, clear regions are also contained in a photo image, so we can correct the subject image by synthesizing (fusing) images that are taken with different object distance (See Fig.1).
Modulated 2 dimensional perfect reconstruction FIR filter banks with permissible passbands

In this paper, the author considers the theory of modulated 2 dimensional (2-D) perfect reconstruction (PR) filter banks with permissible passbands. At first, the author designs a 2-D complex digital filter with half passband obtained by the sampling matrix. Next, 2-D analysis filter banks are realized by modulating this prototype 2-D complex digital filter and by taking the real part of the output. It is also shown that the modulation in the 2-D frequency plane is equivalent to a 1-D DFT. A necessary and sufficient condition for 2-D perfect reconstruction filter banks is derived. Finally, some examples are shown.
Edge-adaptive image interpolation using constrained least squares

Some adaptive image interpolation methods have been proposed to create higher visual quality images than traditional interpolation methods such as bicubic interpolation. These methods, however, often suffer from high computational costs and unnatural texture interpolation. This paper proposes a novel edge-adaptive image interpolation method using an edge-directed smoothness filter. Our approach estimates the enlarged image from the original image based on an observation model. The estimated image is constrained to have many edge-directed smooth pixels which are measured by using the edge-directed smoothness filter introduced in this paper. Simulation results show that the proposal method produces images with higher visual quality, higher PSNRs and faster computational times than the conventional methods.
A new approach for design of paraunitary filter banks with linear phase

In this paper we propose a novel way to design nonparaunitary and paraunitary filter banks so that each individual filter has linear phase. M channel filter banks, which have perfect reconstruction (PR) and linear phase (LP) properties, have been well studied and some design methods were reported. Since almost these methods are based on lattice structures whose sections consist of an orthogonal matrix, the design requires nonlinear programming techniques. Here, we consider a design method which requires only to solve linear equations iteratively. In our proposed method, we minimize the least square error of PR constraints so as to get around using nonlinear programming. We first observe the minimization problem of a quadratic function with two variables. Next, we apply it to the design of nonparaunitary filter banks. Then, we show that this method is applicable to the paraunitary filter banks design with some modification. Several design examples are given to validate our proposed methods.
Design of IIR digital filters in the complex domain by transforming the desired response

In this paper, we present a new design method of IIR digital filters with equiripple magnitude response in the complex domain. This method is based on solving a least square solution iteratively. At each iteration, the desired response is transformed so as to have equiripple error. This algorithm is efficient because we don't need any initial value and any optimization. By this method, a equiripple solution is obtained very quickly with less computational complexity. Finally, we show some examples to validate the proposed method.
Design of signal-adapted linear phase paraunitary filter banks

In this paper, we propose a new design method of signal-adapted filter banks using an adaptive cascade lattice structure. If the filter bank which is well adapted to the signal statistics is used in the subband coding system, we can encode the signal more efficiently than the case using non-adapted one. The purpose of this paper is to design the filter bank which has energy imbalance of each subband. We use the LMS-based adaptive algorithm to design linear phase paraunitary filter banks (LPPUFB) based on a lattice structure.
Two dimensional non-separable adaptive directional lifting structure of discrete wavelet transform

In this paper, we propose a two dimensional (2D) non-separable adaptive directional lifting (ADL) structure of discrete wavelet transform (DWT) and its image coding application. Conventionally, we have proposed a polyphase representation of a 2D non-separable lifting structure of DWT. We generalize the polyphase representation in this paper and one structure of the class has been proven to reduce errors due to the rounding operations and improve a compatibility of the irreversible 9/7 DWT, compared with a 2D separable lifting structure of DWT. Adding the adaptive directional transforming property to the generalized structure, our proposed method improves the lossy image coding performance with maintaining the compatibility.
Image interpolation based on weighting function of Gaussian

In this paper, we propose a new image interpolation method based on a 2-D piecewise stationary autoregressive (PAR) model. SAI, which defined PAR model, is a state-of-the-art method in image interpolation. It produces good quality restored images but has high calculation cost because of solving multiple least-square problems. Our method utilizes Gaussian function in estimating parameters instead of solving least-square problems and reduces the calculation cost. Moreover, parameters are estimated at each pixel, while they are estimated in each local window in SAI. By these improvements, the proposed method has equivalent quality to SAI with low calculation cost.
Generalized unequal length lapped orthogonal transform for subband image coding

Generalized linear phase lapped orthogonal transforms with unequal length basis functions (GULLOTs) are considered. The length of each basis of the proposed GULLOT can be different from each other, whereas all the bases of the conventional GenLOT are of equal length. In general, for image coding application, the long basis for a low-frequency band and the short basis for a high-frequency one are desirable to reduce the blocking and the ringing artifact simultaneously. Therefore, the GULLOT is suitable especially for a subband image coding. In order to apply the GULLOT to a subband image coding, we also investigate the size-limited structure to process the finite length signal, which is important in practice. Finally, some design and image coding examples are shown to confirm the validity of the proposed GULLOT.
A Non-Expansive Convolution for Nonlinear-Phase Paraunitary Filter Banks and Its Application to Image Coding

This paper proposes a new non-expansive convolution for nonlinear-phase paraunitary filter banks (NLPPUFBs). First, we present that any NLPPUFBs can be implemented by connecting several block transforms. Next, we show a signal extension method at the analysis bank by exploiting the characteristics of that structure. Furthermore, we prove that the signal can be reconstructed at the synthesis bank without any redundant signals. Finally, we apply the proposed extension to image coding to validate our method
Sub-pixel shift estimation of image based on the least squares approximation in phase region

This paper proposes a novel method to estimate non-integer shift of images based on least squares approximation in the phase region. Conventional methods based on Phase Only Correlation (POC) take correlation between a image and its shifted image, and then estimate the non-integer shift by fitting the model equation. The problem with using POC is that the true peak of the POC function may not match the estimated peak of the fitted model equation. This causes error in non-integer shift estimation. By calculating directly in the phase region, the proposed method allows the estimation of decimal shift through least squares approximation. Also by utilizing the characteristics of the natural image, the proposed method limits adoption range for least squares approximation. By these improvements, the proposed method improves the estimation and achieves high accuracy.
Design of linear phase with unequal length paraunitary filter banks with suboptimal coding gain

In this paper, we present a design of M-channel linear-phase paraunitary filter banks (LPPUFB), with filters of unequal lengths and same center of symmetry, (ULPPUFB) without using non-linear optimization algorithms. ULPPUFB can be viewed as generalized lapped orthogonal transforms (GenLOTs) with variable-length basis functions and are used in block transform-based image coding. ULPPUFB has long basis functions in order to avoid blocking artifacts, whereas it reserves short basis functions for high-frequency signal components like edges, thereby limiting ringing artifacts. The design of ULPPUFB has already been shown and can be expressed completely using a lattice structure. However, when it is used in image coding, the coding gain must be maximization, and then we must use non-linear optimization algorithms. When filter length or channel numbers are increased, non-linear optimization algorithms would necessitate an enormous amount of calculation. In this paper, we design each filter without using non-linear optimization, directly based on the compaction problem and implement ULPPUFB by changing these filters into lattice structures. Then, we show their validity.
On lattice structure and design of orthogonal and biorthogonal multifilter banks

This paper describes a lattice structure and a design for orthogonal and biorthogonal multiwavelets. First, we factorize the polyphase matrices of symmetric-antisymmetric multifilter bank into elementary low-order building blocks. Second, we transform a tree-structured multiwavelet system into an equivalent scalar filter bank in order to design optimal multifilter banks. Simulation results show that the proposed orthogonal and biorthogonal multiwavelets have superior performance to the popular multiwavelet SA4 and the (9,7)-tap scalar wavelet.
Image interpolation using cosine-sine modulated filter bank

This paper proposes a new image interpolation technique by using direction-aware transform. In literature, it is known that Cosine-Sine modulated filter banks (CSMFB) can be regarded as alternative dual-tree complex wavelet transform, therefore, CSMFB has rich directional selectivity. Our interpolation procedure consists of two stages. First, we generate low frequency image and six directional images from the input image by using 4-channel CSMFB. Then each image is interpolated along with each direction. The simulation results show that our method can produce high visual quality images and improves some artifacts. Moreover, our method is quite feasible from the view point of hardware implementation since there is no branching procedure.
Dynamic bandwidth allocation supporting diversified queue status reporting for EPON systems

Dynamic bandwidth allocation (DBA) is an indispensable function in Ethernet passive optical networks (EPONs). The DBA function implemented in an optical line terminal utilizes REPORT messages to learn about the upstream queue statuses in optical network units (ONUs). However, the methods for describing the REPORT messages are not fully standardized, which results in a lack of interoperability. This paper proposes a diversity DBA technique that can support different types of ONUs with diverse REPORT description methods. The diversity DBA technique is comprised of an identification process to differentiate REPORT description methods and an interpretation process to convert the content of different REPORT description methods. We provide simulation results to demonstrate the validity of the proposed DBA technique.
The quick and high quality image interpolation for single image using multi-filtering and weighted mean

Image upsampling from one input image gathers considerable attention in the field of computer vision. The problem is ill-posed because the number of known low-resolution (LR) pixels is less than that of unknown high-resolution (HR) pixels. Therefore, quality of an upsampled image depends on prior assumptions. Image interpolation methods are one of the image upsampling technologies and are faster than other image upsampling technologies such as Super-Resolution. However, these methods tend to cause jaggies and blurs in edge and texture regions. We use the idea of Multi-surface Fitting (MF) to solve these problems. MF uses plural local functions to estimate an HR pixel and it reduces blurs. Moreover, we utilize filtering instead of calculation of each local function in order to reduce a computational cost. And we introduce new weights to estimate edge directions. By these ideas, our method has both high quality and a low computational cost.
Image noise level estimation by searching for smooth patches with discrete cosine transform

When denoising an image, noise level is one of the most vital input parameters, because setting wrong noise level affects a result of denoising. Therefore, the noise level must be estimated accurately. In this paper, we propose a new accurate noise level estimation method based on the characteristic of discrete cosine transform (DCT) coefficients. This characteristic is that the high-frequency coefficients of the smooth patches can be assumed to zero. We select smooth patches from a distribution of the standard deviation of high-frequency coefficients in a noisy image, and a distribution function of the standard deviation of high-frequency coefficients in an only noise image. Moreover, we propose a method that the estimated noise level is calculated from high-frequency coefficients in a noisy image. The experiment results with many images demonstrate that the proposed method estimates the noise levels more accurately, in comparison with the conventional methods.
Design of linear phase paraunitary filter banks with suboptimal coding gain without nonlinear optimization

First, we design a low-pass filter with some regularities and then M/2-1 highpass and bandpass filters are designed such that each filter has minimum compaction gain. The cost function which consists of the frequency constraint, orthogonal condition and the variance of output signal is expressed in quadratic form of the filter coefficients. Consequently, the cost function can be minimized by solving linear equations iteratively without using nonlinear optimization.
Design and implementation of cosine-modulated 2 dimensional perfect reconstruction FIR filter banks

It is well known that FIR filter banks, satisfying the perfect reconstruction (PR) property, can be obtained by cosine modulation of linear-phase prototype FIR digital filter. In this paper, it is shown to be possible to design 2-dimensional (2-D) PR filter banks using cosine modulation as for the 1-D case. At first, the author designs a 2-D digital filter with half passband obtained by the sampling matrix. Next, 2-D analysis filter banks are realized by cosine-modulating this prototype 2-D digital filter. It is shown that the modulation in 2-D frequency plane is equivalent to the 1-D modulation. A necessary and sufficient condition for 2-D perfect reconstruction filter banks is derived. Furthermore the author formulates the design method as a quadratic-constrained least-square minimization problem.<<ETX>>
Decorrelating compensation scheme for coefficient errors of a filter bank parallel A/D converter

A parallel A/D conversion scheme with a filter bank for low-IF receivers is presented. The analysis filters of the filter bank divide the frequency components of the received signal, and achieve parallel A/D conversion. Therefore, the required conversion rates and the resolution of the A/D converters can be reduced and the receiver can demodulate wideband signals. As the analysis filters consist of analog components, their coefficients include errors. These errors cause mutual interference between signals in orthogonal frequencies. In order to remove this interference, a decorrelating compensation scheme is proposed.
Image denoising by arithmetic means based on similarity

In this paper, we propose a Non-Local Means algorithm-based denoising method. In conventional NLM, the weighting functions are acquired based on the similarity between target patch and its neighboring patches and then Gaussian-range kernel is calculated based on the similarity. Then, target patch is replaced by weighted means value of neighboring patches. In comparison, our method extracts similar patches by thresholding and only calculates simple arithmetic average. The method does not only outperform the conventional NLM but also implement with less computation. Finally, we compare the proposed and the conventional NLM, and validate the advantage.
Design of generalized linear-phase paraunitary filter banks with zeros at mirror frequencies

In this paper, we present a novel lattice structure and design of the linear phase M-channel paraunitary filter banks whose filters all have zeros at the mirror frequencies except for the passband. This structure is implemented by replacing the first block of the lattice structure with two type II DCTs. With this structure, the filter banks are implemented with high speed and are designed without taking account of the stopband attenuation. Finally, we show some examples to validate the proposed method.