nils-herrmann/clean_scirepeval huggingface dataset:
Color image coding based on linear combination of adaptive colorspaces

This paper improves a colorization-based image coding using image segmentation and adaptive colorspaces. Recently, various approaches for color image coding based on colorization have been presented. These methods utilize a YCbCr colorspace and transfer the luminance component by a conventional compression method. Then, the chrominance components are approximated from the luminance component using a colorization method. Our method segments a luminance component into small segments called superpixels, and reconstructs the chrominance of each superpixel as a linear combination of its luminance. For chrominance components, we introduce an adaptive color space transform optimized for liner combination. This is because YCbCr colorspace cannot always become a good approximation of the chrominance. In addition, we introduce an automatic selection for the number of superpixel segments from a given quality factor. The simulation with standard images shows that our method performs better result than conventional coding schemes.
Content aspect ratio preserving mesh-based image resizing

We proposed a novel method for content-aware image resizing based on grid transformation. Our method moves each vertical and horizontal grid lines in the perpendicular direction to itself. Keeping important regions unchanged is a strong constraint for image resizing. Satisfying this constraint can produce significant distortion on unimportant regions. Our method allows important regions to be changed and suppresses the changes of the aspect ratios of important regions. In addition, we introduced the lower thresholds of the scaling rates of grid meshes and the boundary discarding process. Experimental results demonstrate that our proposed method resizes images with less distortion than other resizing methods.
Direction scalability of adaptive directional wavelet transform: An approach using block-lifting based DCT and SPIHT

Adaptive directional wavelet transform is an effective alternative of the traditional 2-D wavelet transform for image coding. It is able to transform an image adaptively along diagonal orientations as well as conventional vertical/horizontal directions. However, it requires to transmit transform direction information to the decoder side. For image coding at very low bitrates, the bit budget of the direction information degrades a reconstructed image quality. In this paper, a method to construct a scalable bitstream for transform directions is presented. We utilize the fact that the matrix yielded by transform direction indices still contains the original image characteristics. The matrix is transformed by a block-lifting based DCT, then encoded by SPIHT to yield a scalable bitstream. Our method is effective for very low bitrate image coding, and is comparable to the non-scalable one for middle-to-high bitrates.
Vocal separation by constrained non-negative matrix factorization

The vocal separation is to separate vocal part and remove the accompaniment part from the mixed music data. Vocal part include many information, singer, lyric and emotion of the song. If we can extraction only the vocal part from the original sound from CD source, it can be applied to various applications. In this paper, we propose a new method to take out the natural vocal parts from mixed music by using non-negative matrix factorization (NMF). This NMF-based framework separates the harmonic, percussive, and vocal structures from the input signal. We impose the constraint into each component to enforce its feature such as harmonic or temporal continuity. In addition, we propose a framework utilizing the prior information in order to achieve the valid vocal separation over this mathematical procedure. The experiments over some vocal databases show the proposed framework has the superior separation performance compared to the conventional methods. Also by considering the characteristics of music, we intend to obtain high accuracy result.
Modulated 2 dimensional perfect reconstruction FIR filter banks with permissible passbands

In this paper, we present a design method of 2 dimensional (2-D) perfect reconstruction (PR) filter banks with permissible passbands by modulating a complex prototype 2-D FIR digital filter. At first, we design a 2-D complex digital filter with half of a passband obtained by a sampling matrix. Then, we show that the 2-D analysis filter banks can be realized by modulating this prototype 2-D complex digital filter and taking the real part of the output. It is demonstrated that the modulation in 2-D frequency plane is equivalent to one dimensional (1-D) discrete-Fourier-transform (DFT). We also derive a necessary and sufficient condition for the 2-D PR filter banks.
Blind image deconvolution using specified HPF for feature extraction and conjugate gradient method in frequency domain

Image deconvolution is the task to recover the image information that was lost by taking photos with blur motion. Especially blind image deconvolution requires no prior informations other than the blurred image. This problem is seriously ill-posed and an additional operation is required such as extracting image features. In this paper, we present a blind image deconvolution framework using a specified highpass filter (HPF) for feature extraction to estimate a blur kernel. This problem can consider the kernel estimation in the region where salient edges are not present and improve the quality of the estimated kernel. Our approach also accelerates the deconvolution process by utilizing a conjugate gradient method in a frequency domain. This process eliminates costly convolution operations from the iterative updating and reduces the calculation time. Evaluation for 20 test images shows our framework not only performs faster than conventional frameworks but also improves the quality of recovered images.
Fractional cycle spinning via modulated lapped transform for overcomplete image representation

This paper aims to introduce an overcomplete transform based on fractional cycle spinning (FCS). Conventionally, the CS approach of wavelet transforms has been proposed, in order to achieve translation invariance with redundancy, unlike the classical critically sampled wavelet transform. This advantage contributes to efficient image processing, such as image denoising. The proposed FCS generalizes CS and show that richer overcompleteness can be provided by fractional shifts of input signals. For realizing fractional delay, we present the approach based on modulated lapped transforms (MLTs). It is shown that their filter kernels can express arbitrary fractional delay by carefully selecting their window function. In addition, this paper extend the conventional MLT to the dual-tree MLT to improve its poor directional selectivity. Then, an efficient lattice structure for the FCS is described for lower computational complexity. Finally experimental results show FCS can be applied better than the conventional CS in image denoising.
Quadtree-Structured Motion Estimation Based on Phase Correlation

This paper proposes a new quadtree-structured motion estimation method based on a phase correlation . In the conventional video coding scheme like MPEG series/H.26x, they use block-matching (BM) motion compensation and the frequency transform. But the problem of the conventional BM method in the part of motion compensation is the computational demanding task. We aim to reduce the computational times and present a novel quadtree-structured phase correlation motion estimation. Phase correlation method is very computationally efficient than the BM method. Quadtree hierarchy scheme reduces not only motion compensated errors but also the computational complexity. Through some examples, our proposed method provides a good compression performance and reduction of computational times as compared to BM method that minimizes sum of squared difference (SSD)
Image denoising by adaptive directional lifting-based discrete wavelet transform and quantization

In this paper, we propose the non-local method for image de-noising via adaptive directional lifting-based discrete wavelet transform (ADL) and quantization. The non-local methods such as non-local means are interested in image denoising based on the self-similarity. They search similar blocks and estimate the original value. The proposed method doesn't search but generates new similar blocks by ADL with multiple directions, and quantization to denoise. It improves the denoising quality and reduces the computational complexity. Finally, we compare the proposed and conventional method, and show an advantage of them.
$M$-Channel Nonlinear Phase Filter Banks in Image Compression: Structure, Design, and Signal Extension

This paper describes a transform coding technique based on M-channel perfect reconstruction filter banks with a nonlinear phase. In contrast with linear-phase filter banks, the nonlinearity provides an extra degree of freedom that can be used to design a more efficient transform. We present new lattice structures of paraunitary and perfect reconstruction (biorthogonal) filter banks, which can be implemented with a lower computational complexity and/or represented by a few free parameters, through the decomposition of the lattice blocks and the displacement across the delay block. We further discuss a smooth extension method for nonlinear-phase filter banks to obtain a nonexpansive transform. The promise of our proposed approaches is demonstrated through several design examples, extended signals and compression results
Design of 2-dimensional linear phase perfect reconstruction FIR filter bank using Lagrange multiplier method

We present a design method of 2-dimensional (2D) linear phase (LP) perfect reconstruction (PR) FIR filter banks based on the Lagrange multiplier method. In M analysis filters, we first design M-1 analysis filters which have an LP property. Finally we design the Mth analysis filter with LP so that the overall system satisfy PR. Then the Mth analysis filter is optimized to have a good response while keeping PR based on the Lagrange multiplier method. By this method, 2D LP PR filter banks can be easily designed by only solving the simultaneous equation, although the order of the Mth analysis filter is higher than that of the others.
Reversible Symmetric Nonexpansive Convolution: An Effective Image Boundary Processing for  $\mbi{M}$ -Channel Lifting-Based Linear-Phase Filter Banks

We present an effective image boundary processing for M -channel (M ε ℕ, M ≥ 2) lifting-based linear-phase filter banks that are applied to unified lossy and lossless image compression (coding), i.e., lossy-to-lossless image coding. The reversible symmetric extension we propose is achieved by manipulating building blocks on the image boundary and reawakening the symmetry of each building block that has been lost due to rounding error on each lifting step. In addition, complexity is reduced by extending nonexpansive convolution, called reversible symmetric nonexpansive convolution, because the number of input signals does not even temporarily increase. Our method not only achieves reversible boundary processing, but also is comparable with irreversible symmetric extension in lossy image coding and outperformed periodic extension in lossy-to-lossless image coding.
2-D local cosine bases with K-regular

Although the study on 2-D local cosine bases (LCB) is referred to, it is a special case in which a sampling matrix is restricted. We impose the K-regular condition on the theory of the 2-D cosine modulated perfect reconstruction filter bank. On this condition, we propose an algorithm which achieve the 2-D local cosine bases with a number of arbitrary divisions (sampling matrix). We also propose to make it regular by imposing the multi-zeros (K-zeros) condition in the aliasing frequency on the lowpass filter of the cosine modulated 2-D perfect reconstruction filter bank.
Colorization-based image coding based on superpixel

This paper proposes a novel colorization-based color image coding method. This method segments an input image into small segments called superpixels and restores the chrominance of each superpixel as the linear transformation of its luminance. A lot of color image coding methods using colorization have been proposed, but no methods utilize a local correlation between the luminance component and the chrominance component effectively. Therefore conventional methods cannot recover the information of local variation and the output image becomes excessively smoothed. We introduce the region segmentation to suppress large fluctuations in the segmented area. This segmentation makes possible to restore the chrominance from the luminance using a linear transformation. The simulation with some standard images shows that the framework actually performs better result than the conventional algorithms based on JPEG.
Generalized lapped biorthogonal transforms using lifting steps

A large class of lapped biorthogonal transforms using lifting steps (LLBT) is presented. The transform coefficients are parametarized as a basic matrix and a series of lifting steps, providing fast, efficient in-place computation of them. Our main motivation of the new transform is its application in image coding. The LLBT has several long overlapped basis functions of the synthesis bank for representing smooth signals to avoid annoying blocking artifacts. The bases of the synthesis bank covering high-frequency bands are constrained to be short to reduce ringing artifacts. Moreover, the analysis bandpass filters provide better stopband attenuation. Comparing to the popular 8/spl times/8 DCT, the LLBT only requires several more additions and shifting operations. However, image coding examples show that the LLBT is far superior to the DCT and 8/spl times/16 LOT in both objective and subjective coding performance.
Cosine-modulated 2-dimensional perfect reconstruction FIR filter banks with linear phase

In this paper, we propose a design method of cosine-modulated 2-dimensional (2-D) perfect reconstruction (PR) FIR filter banks, in which each analysis and synthesis filter has linear phase (LP). As in previous works, it is impossible to design the 2-D cosine modulated system which satisfies both the PR condition and LP property. However, in 2-D signal processing, it is very important for each filter to have the LP property. Our main goals are to show such a system can be realized by considering a new decomposition scheme and derive the conditions for PR and LP. A design example is included to show the effectiveness of this paper.
Structurally regular integer discrete cosine transform for low-bit-word-length coefficients

This paper presents an IntDCT with only dyadic values such as k/2n (k, n 6 N). Although some IntDCTs have been proposed, they are unsuitable for lossless-to-lossy image coding in low-blt-word-length (coefficients). First, the proposed M-channel lossless WHT (LWHT) can be constructed by only (log2 M)-blt-word-length and has structural regularity. Then, our 8-channel IntDCT keeps good coding performance even In low-blt-word-length because LWHT, which Is main part of IntDCT, can be implemented by 3-bit-word-length. Finally, our method is validated In lossless-to-lossy image coding.
Noiseless no-flash photo creation by color transform of flash image

In the dark place photographing, the increase of noise is one of the major problems to be addressed. Although using a flash is effective to reduce the noise, natural colors are faded away due to increase of specular lights. In this paper, we present a method that generates a no-flash like flash image by approximating colors of a flash image by those of a no-flash image. Our method is based on the ”color-line” feature of images, a linear distribution of colors in a local region is transformed by a set of transform matrices automatically. This method is able to deal correctly with the occluded regions where the colors are saturated by reflections or shadows and the color distribution is squashed.
A novel lattice structure of M-channel paraunitary filter banks

In this paper, we present a novel lattice structure of M-channel paraunitary filter banks. M-channel paraunitary filter banks without imposing the linear phase constraint outperform the linear phase paraunitary filter banks in image coding. Removing the redundancy of the lattice structure in filter banks, the complete and minimal structure is derived. Based on this structure, the pairwise mirror-image filter banks are also derived by restricting the rotation angles. Finally we show some examples to validate the proposed method.
Factorization of nonuniform block orthogonal transforms

Block orthogonal transforms (BOTs) are commonly used for lots of applications. Conventional BOTs are based on uniform filter banks, however, nonuniform BOTs are often superior to uniform ones. In this research, we investigate the factorization of nonuniform BOTs which does not involve the tree structure. Therefore, optimal nonuniform BOTs are available in the sense of transform coding gain. Some design examples are included to confirm our theory. We also apply the nonuniform BOT to the transform image coding.
Blocking artifacts reduction of DCT compressed image based on block wiener filtering

In this paper, a novel de-blocking algorithm is proposed, using block wiener filtering, shift and weighted average operations. The dissipation of block boundary occur by a combination of the shift and average operations. However, visually annoying artifacts are noticeable around the edge region in highly compressed images. In the proposed method, the wiener attenuation coefficients are given based on the estimated error in a block unit. The DCT encoded images have a large margin of error from one block to another. Hence texture information losses are prevented while smoothening effect is applied to the region around the edge. In examples, the proposed algorithm shows better performance than the previous one.
Design of perfect reconstruction FIR filter banks using DFT-modulation

In this paper, we present a design method of perfect reconstruction (PR) FIR filter banks by discrete Fourier transform modulation (DFT-modulation). In a previous work, the implementation of cosine-modulated PR filter banks was shown to be easy to design and capable of fast processing. But this method is a little bit inconvenient because of its restriction on the filter length. In our new approach filter banks are implemented by DFT-modulation of a prototype filter with complex coefficients and this has some advantages over the previous work. Furthermore, we propose a optimization method using the Lagrange-Newton method. Finally, we give a design example and show this method to be effective.
Iterative procedure for designing the GenLOT

In this research, we propose a new design method for the generalized linear-phase lapped orthogonal transforms (GenLOT). The GenLOT is based on the DCT and has fast implementation algorithm. Generally, the lattice structure is used for its design and implementation. Consequently, nonlinear optimization is required for its design process. In our proposed method, filter coefficients are optimized directly and this method requires one only to solve linear equations iteratively. Moreover, this algorithm converges within a few iterations.
On factorizations of conjugate symmetric Hadamard transform and its relationship with DCT

Complex-valued conjugate symmetric Hadamard transform (C-CSHT) is a variant of complex Hadamard transform and effective for some signal processing and communication applications. Its closed-form factorization of the general N-channel (N = 2m) case was recently proposed, however, there still exist a room to find an effective factorization especially for unified factorization of C-CSHT and its real-valued transform counterpart (R-CSHT). In this paper, we present another simple closed-form factorization of C-CSHT based on that of R-CSHT. The proposed factorization is applicable for both complex- and real-valued CSHTs with one factorization. Furthermore, the relationship with the common block transform, DCT, is revealed.
NMF-based multiple pitch estimation using sparseness and inter-frame continuity constraints

This paper proposes NMF-based (non-negative matrix factorization) multiple pitch estimation algorithm. The approach of NMF-based multiple pitch estimation is to decompose input magnitude spectrogram into sum of basis spectra representing individual pitches. In decomposing music signals, the amplitude of basis spectra should have sparseness, and the shape of amplitude should be continuous between neighbor temporal frames. We introduce the constraint using matrix norm to enforce these characteristic at once and propose new NMF algorithm for spectral decomposition with this constraint. The evaluation of solo piano music shows this algorithm can implement more robust pitch estimation in the place which input spectrum has certain different shape from basis spectra or the shape of input spectrum has temporal change.
Noise removal based on surface approximation of color line

In a local region of a color image, the color distribution often takes the form of a linear line in the RGB space. We call this property "Color Line". We propose a denoising method based on this property. When the noise is added on an image, the color distribution spreads from Color Line. The denoising is achieved by reducing the spread. In conventional methods, Color Line is assumed to be only a single line, but actual distribution takes various shapes such as a single line, two lines, and a flat surface and so on. In our method, we estimate the distribution in more detail using surface approximation and denoise each patch by reducing the spread depending on the color distribution types. In this way, we can achieve better denoising result than a conventional method.
Smooth signal extension for M-channel paraunitary filterbanks and its application to image coding

In the transform-based image coding, the symmetric extension is important to obtain subband signals effectively without increasing the total number of signal. However in the case of the symmetric extension, subband filters have to be (anti-)symmetric. This means that the linear phase property is strict constraint on filters' impulse response for the symmetric extension. For the other method of the signal extension, the periodic extension is implemented. While it can be applied to any filters, it introduces artificial discontinuities at the signal boundaries. In this paper, we present a smooth extension for M-channel filterbanks to implement nonexpansive decomposition. First, we derive a condition for solving the coefficient expansion problem. Second, we calculate a smooth extended signal under the condition by singular value decomposition. Finally, we design 8 channel 16 tap paraunitary filterbank using lattice structure, and several image coding and extended signal examples are shown to confirm the validity of the proposed approach.
A Generalized Lapped Transform with Unequal Length Filters based on First-Order Linear-Phase Filter Banks

In this paper, we propose design methods for biorthogonal linear-phase filter banks (BOLPFBs) which have unequal length filters in their synthesis banks or in their both (analysis and synthesis) banks based on first-order linear-phase filter banks (FOLPFBs). First, we indicate that the building blocks in FOLPFBs can be used as those in variable-order LPFBs (VOLPFBs). Second, we propose a VOLPFB which have unequal length filters in its synthesis bank (UVLPFB). Long highpass filters of a synthesis bank often generate the ringing artifacts. Ringing artifacts are a main disadvantage in image coding based on FOLPFBs. Since UVLPFBs have long lowpass filters and short highpass filters in their synthesis bank, they can reduce the ringing artifacts as well as approximate smooth regions well.