nils-herrmann/clean_scirepeval huggingface dataset:
Misaligned Image Integration With Local Linear Model

We present a new image integration technique for a flash and long-exposure image pair to capture a dark scene without incurring blurring or noisy artifacts. Most existing methods require well-aligned images for the integration, which is often a burdensome restriction in practical use. We address this issue by locally transferring the colors of the flash images using a small fraction of the corresponding pixels in the long-exposure images. We formulate the image integration as a convex optimization problem with the local linear model. The proposed method makes it possible to integrate the color of the long-exposure image with the detail of the flash image without causing any harmful effects to its contrast, where we do not need perfect alignment between the images by virtue of our new integration principle. We show that our method successfully outperforms the state of the art in the image integration and reference-based color transfer for challenging misaligned data sets.
Design of linear phase FIR filters using the nonuniform DCT

We propose a novel interpolation technique for the design of linear phase FIR filters on nonuniform frequency grids. In this paper, we introduce the NDCT and propose an efficient way to implement it. In our method, the interpolation problem is converted into the one of constructing orthonormal functions. The computational complexity is O(N/sup 2/) which is comparable with the Lagrange and Newton interpolation methods. The advantage over the other interpolation techniques is that one can easily apply this method to a least squares approximation on nonuniformly frequency grids by truncating filter coefficients.
Image Compression Suitable for High Dynamic Range Image Rendering

In this paper, we propose a high dynamic range image coding method based on wavelet compression. In our method, we employ a pre-processing function to minimize errors between rendered (i.e. tone mapped) version of an original and compressed images. To enhance efficiency of the coding, we introduce the Hill function as the pre-processing. This function partially compresses the dynamic range of the HDR images based on the human visual system. The method implicitly assigns more bits to visually important luminance regions. We show the validity of our preprocessing by some experimental results.
Lossless/near-lossless color image coding by inverse demosaicing

In this paper, we introduce a novel framework for lossless/near-lossless (LS/NLS) color image coding assisted by an inverse demosaicing. Conventional frameworks are typically based on prediction (and quantization for NLS coding) followed by entropy coding, such as the JPEG-LS for bit rate saving. The approach of this work is totally different from the conventional ones. Basically, color images are created by demosaicing Bayer-pattern color filter array (CFA) whose operator can be expressed as square matrices. By using the (pseudo) inverse matrix of a joint demosaicing and color-to-gray conversion, the proposed decoder can recover the color image from its corresponding gray image data which is losslessly transmitted by the proposed encoder. Thus, LS/NLS color image reconstruction can be achieved while saving a bit rate significantly. In addition, using the same framework of color image coding, LS/NLS CFA coding can be realized by a comparable bit rate with JPEG-LS.
Complex approximation of FIR digital filters by updating desired responses

In this correspondence, we present a new numerical method for the complex approximation of FIR digital filters. Our objective is to design FIR filters whose absolute error between the designed and desired response is equiripple. The proposed method solves the least-squares problem iteratively. At each iteration, the desired response is updated so as to have an equiripple error. The proposed methods do not require any time-consuming optimization procedure such as the quasi-Newton methods and converge to equiripple solutions quickly. Moreover, by multiplying the arbitrary weighting function on the desired response of the passband and stopband, the errors in the passband and the stopband can be controlled. We show some examples to illustrate the advantages of our proposed methods.
Texture classification and resolution control for 3S urban map

This paper proposes a method to control texture resolution for rendering large-scale 3D urban maps. Recently, performance of computers has been developed rapidly, but it is still hard to directly handle the large-scale 3D maps on PCs, because of its high requirement for hardware capability. Thus the data reduction is essential for rendering of the large map. Since on the 3D maps, texture data, in general, tend to be far larger than geometry data, it is more effective to reduce the texture data by exploiting the LOD (level of detail) in order to decrease whole data size. To achieve this, we propose a method to control the resolution of the texture. In our method, the textures are classified into some classes. The appropriate texture resolutions are decided according to their rendered sizes on a display and their importance, and the classes they belong to. We verify the validity of our resolution control method by some experiments.
Local color distribution projection filtering using a homogeneous coordinate system

In this paper, we present a denoising method of using multiple image composition based on the color transform of local color distribution of patches. In the method, the color of a guidance image is transformed so as to get close to a noisy input image by a patch-wise color transform. As a result, a noiseless image is obtained. Actually this method can be regarded as the generalized version of our previous method  and the guided filter , and gives improved images with more clear appearance. The existing methods have a restriction that a filter output form is expressed only by a linear transform, i.e., a first order polynomial. In this paper, we introduce a more general formula for this category of filtering with the guidance image. We deal with a quadratic formula for realizing more flexible transform instead of the previous linear transform, and moreover introduce more simple and flexible regularization.
Time-varying wavelet transforms with lifting steps for lossless image compression

Most natural images are well modeled as smoothed areas segmented by edges. The smooth areas can be well represented by a wavelet transform with high regularity and with fewer coefficients which requires high-pass filters with some vanishing moments. However for the regions around edges, short highpass filters are preferable. In one recently proposed approach, this problem was solved by switching filter banks using longer filters for smoothed areas of the images and shorter filters for areas with edges. This approach was applied to lossy image coding resulting in a reduction of ringing artifacts. As edges were predicted using neighboring pixels the nonlinear transforms made the decorrelation more flexible. In this paper we propose a time-varying filterbank and apply it to lossless image coding. In this scheme, we estimate the standard deviation of the neighboring pixels of the current pixel by solving the maximum likelihood problem. The filterbank is switched between three filter banks, depending on the estimated standard deviation.
A New Encoding Scheme for HDR Images

Human eye can perceive a much higher dynamic range compared to what can be displayed on paper or a computer screen. Recently, advanced techniques have been available to capture much larger amount of details of natural scenes. These images are then tone-mapped to lower dynamic range versions for displaying on paper or a screen. For certain applications, available now or expected in near future, the additional information contained in the higher dynamic range images is also important, and needs to be preserved. However, the size of these images is very large and that gives rise to need of special encoding techniques for these images. In this paper, we present such a technique, which significantly reduces the size of the high dynamic range images, with a negligible loss of information. Comparison with the existing state of the art technique is given to show the effectiveness of our proposed scheme.
Improved kinematics based motion compression for human figure animation

This paper presents an improved kinematics based motion compression algorithm by using key frame extraction. In a motion chain, the movement of each joint is represented by a series of curves in 3D space. In general, when compressing the motion data, the distortion of parent joint caused by quantization in turn affects its child joint and is accumulated to the end effector. The inverse kinematics based method can address this problem well. Moreover, to achieve a higher compression rate, we propose a period detection method and a key-frame extraction method into 3D position curves of end effectors. Our method automatically detects the key frames in motion curves of end effectors using frame decimation. Combining inverse kinematics technique and key frame extraction method, our method achieves efficient compression with a high compression rate and high quality of the motion data. By comparing with a conventional prediction we demonstrate the advantage of ours with some examples.
New design of FIR digital differentiators having maximally linearity at middle of the frequency band

Maximal linear FIR digital differentiators are preferred over others, like minimax designs, for narrow band applications. Most of the existing maximally linear designs achieve maximal linearity at zero frequency, and relatively lower attention has been given to the designs accurate in mid and higher frequency bands. We present a simple design accurate for midband frequencies, by forcing the maximal linearity constraints at half of the Nyquist frequency. The design problem is formulated as the solution of a system of linear equations, obtained by imposing maximal linearity constraints to the general frequency response of the filter. Certain special characteristics of the determinant of the coefficients matrix of these equations are explored and used in derivation of the explicit formulas for the impulse response coefficients.
Flash/no-flash image integration using convex optimization

When high ISO sensitivity is used to acquire images of dark scenes, their detail textures are often deteriorated by sensor noise. On the other hand, using flash photography with artificial light, one can shorten the exposure time, and obtain a sharp image under the low ISO sensitivity. However, the use of flash light changes the color tone and often generates unnatural images due to a specific color temperature of the additional light. This paper presents a new efficient method for flash/no-flash image integration. In contrast to conventional integration methods assuming that the flash image has a sharp texture without any noise, our method can successfully remove noise. Specifically, our method separately handles regions within the reach of the flash light and other regions out of range of the flash light, because the two regions have much different characteristics. As for the former well-exposed regions, we transferred the detail of the flash image to no-flash image by optimization and component separation. As for the latter under-exposed regions, an optimization based joint bilateral filtering that uses information of a flash image is performed to remove noise. Experimental results show the effectiveness of our method compared to the conventional methods.
FFT based solution for multivariable L2 equations using KKT system via FFT and efficient pixel-wise inverse calculation

When solving l2 optimization problems based on linear filtering with some regularization in signal/image processing such as Wiener filtering, the fast Fourier transform (FFT) is often available to reduce its computational complexity. Most of the problems, in which the FFT is used to obtain their solutions, are based on single variable equations. On the other hand, the Karush-Kuhn-Tucker (KKT) system, which is often used for solving constrained optimization problems, generally results in multivariable equations. In this paper, we propose a FFT based computational method for multivariable l2 equations. Our method applies a FFT to each block of the KKT system, and represents the equation as an image-wise simultaneous equation consisting of Fourier transformed filters and images. In our method, an inverse matrix calculation that consists of complex pixel values gathered from each transformed image is required for each pixel. We exploit the homogeneity of neighboring values and solve them efficiently.
Constrained design of FIR filters with sparse coefficients

We present an algorithm for the constrained design of FIR filters with sparse coefficients. In general, the filter design approach aims to minimize a filter order and maximize the filter performance. Although the FIR filter coefficients designed by the least squares method is optimal in the least squares sense, it is not necessarily optimal among the set of filters with the same number of multipliers, that is, less mean squared error can be achieved by a filter that has the same number of multipliers, but has longer impulse response with some zero-valued entries. Our method minimizes the number of nonzero entries in the impulse response together with the least squares error of its frequency response. In addition, we incorporate some constraints to the design and realize better performance than conventional constrained least squares design.
Image coding using wavelets based on two-channel linear phase orthogonal IIR filter banks

In this paper, we focus on two-channel perfect reconstruction IIR filter banks. Often two-channel FIR filter banks with additional characteristics such as the perfect reconstruction property and linear phase are used in subband systems. This type of filter banks belongs to the class called biorthogonal filter banks. While several works have pointed out that the perfect reconstruction IIR filter banks have both linear phase and orthogonality, the linear phase orthogonal IIR filter banks have never been applied to image coding. Then we apply the two-channel perfect reconstruction IIR filter banks consisted of allpass filters, with both linear phase and orthogonality, to image coding and show that the proposed IIR filter bank with 3 zeros at z=1 for the analysis lowpass filter, has less computational complexity and produces better results in terms of PSNR than the FIR filter bank, namely the two-channel linear phase biorthogonal (9,7)-taps. Consequently both linear phase and orthogonality are essential to improve coding performance.
Texture Simplification in 3D Maps for Visualization at Low Resolution

Three-dimensional (3D) urban models, come with huge data size, mainly consisting of the information of geometry and the texture, and the simplification of both is often needed for efficient streaming, rendering and visualization. In this paper, we present different techniques for simplification of different types of the texture images in 3D urban maps, aiming at their visualization on low resolution screens, such as those of the cell phones. We sort the images into two different classes based on their certain features, and develop suitable simplification techniques for each class. The simplified images preserve the main features and have significantly smaller size as compared to the originals
Frequency spectrum regularization for pattern noise removal based on image decomposition

This paper deals with a mixed norm of complex vectors, i.e., the sum of amplitude spectra, and its minimization problem. A combination of this mixed norm and image decomposition problem works well for reduction and decomposition of pattern noise that arises when scanning old photographs with granulated surface. Generally, the spectral distribution of natural images decreases smoothly from low frequency band toward high frequency band, while that of pattern noise is distributed sparsely. Therefore, we assume that an observed image consists of a latent image component and a pattern noise component, and characterize them by using the total variation function and the proposed function, respectively. This enables a reasonable decomposition of the two components. Compared to similar decomposition methods such as Robust PCA, our method has a good decomposition accuracy for this task, and low computational cost.
A compact format for coding of texture in 3D urban models

Three-dimensional (3D) urban models, come with huge data size, mainly consisting of the details of geometry and texture of the objects, and simplification of both is often needed for efficient streaming, rendering and visualization. A large number of objects in 3D urban models are buildings and the image files representing their texture contain information of the walls, streets, doors, and windows etc., which have linear edges. We present a technique to identify the images representing the texture of these objects, and propose a compact format to encode them in much smaller size compared to the existing standard image formats.
A study on joint progressive coding of range data and texture images

This work presents a joint progressive coding of range and texture images. We use the method that decomposes the range and texture images in hierarchical structures using wavelet transform and scales up pixels of texture by using the information of the range images coded by EZW-IP. This coding method enables an efficient coding and progressive scalability representation of a 3D model. We apply this proposed method to range and texture images acquired by laser range finders and show the validity of this method.
Eigen-model based 3D model recognition from cylindrical mapped image

In this paper, we present a new method for 3D model recognition. Unlike other approaches, our model recognition is accomplished based on a plane which describes a 3D model and an eigen-model algorithm. By mapping a 3D model into a virtual cylinder around the model, we get the 3D model aspect information on an unfolded cylinder as a 2D image, which gives effective data format for feature extraction, selection and classifier design phases. We apply automatic optimal feature selection and a hierarchical database organization from the SHOSLIF algorithm to 3D object recognition.
Digital differentiators for narrow band applications in the lower to midband range

Ripple designs of FIR digital differentiators are suitable for wideband applications, but cannot produce very high accuracies in narrow bands. In this paper, we present new simple designs for FIR digital differentiators, with very high accuracies in the narrow bands centered at arbitrary frequencies in the lower half of the frequency band. First, a new design with maximal linearity at the middle of the frequency band is presented, by imposing the maximal linearity constraints to the frequency response. This design is then combined with an existing design having maximal linearity at zero frequency, to obtain differentiators with very high accuracies at arbitrary frequencies in the lower half of the frequency band. Explicit formulas for the filter coefficients are derived, and design examples are presented to show their higher accuracies as compared to the existing designs.
Design of nearly linear phase IIR digital filters with prescribed log magnitude response

In this paper, we propose a new design algorithm for nearly linear phase IIR digital filters with prescribed log magnitude response. The error function used here is the sum of the weighted log magnitude-squared error and phase-squared error, and so it is possible to control log magnitude and phase response directly. The gradient vector of the proposed error function is easily calculated as the closed form solution because of its nature, in which the real and imaginary part of the logarithm of a complex transfer function corresponds to the log magnitude and phase response, respectively. This algorithm is simple and converges quickly. Finally, we show the validity of the proposed algorithm with some examples.
Simplification of texture in 3D maps

In this paper, we present a numerical technique for simplification of the texture of 3D maps. In the simplification process, we first select textures that can be segmented by straight lines using Hough transform. The selected texture images are simplified by the Hough transform. The other texture are filtered by the anisotropic diffusion and then the details are removed to reduce their data sizes. The representative colors of the image are chosen from the image, and the image is quantized based on those colors. The simplified image, with all major features of the original image preserved, has much smaller size as compared to the original.
Quantum-confined field-effect light emitters: device physics and experiments

Extended experimental results on three-terminal quantum-confined field-effect light emitters with current injection and field control of luminescent characteristics in the quantum-well structure are reported. By incorporating superlattice buffer layers (SLBLs), the quantum efficiency of the device is dramatically improved and equivalently nonradiative recombination processes are sufficiently suppressed at room temperature. The red-shift of the emission spectra by the quantum-confined Stark effect assures that the electric field is effectively applied to the quantum well. The experimental data on the transient responses of emission intensity to input voltage pulses show fairly good correspondences with theoretical prediction and previous photoluminescence experiments. The authors discuss the ultimate capability of high-speed switching and point that an optical pulse with a duration as short as 30 ps and involving more than 100 photons can be generated by scaling down the size of the device with 1% external efficiency.
Lossless compression of LogLuv32 hdr images by simple bitplane coding

A method of lossless compression of high dynamic range (HDR) images encoded in LogLuv32 format is presented. Simple bitplane coding (SBC) is independently applied to the components of LogLuv data. A context model for coding a bit is created by a comparison of neighboring pixel values, and is fed to a range coder. As a result, the average bit rate of 9.8 bits/pixel was obtained in lossless compression of popular 34 LogLuv32 HDR images. That is, a set of those data shrinks to 31% of the uncompressed data size on average.
An automatic yearbook style photo generation method using color grading and guide image filtering based facial skin color correction

In this paper, we propose an automatic photograph generating method for albums of large numbers of people, which gives consistency to facial skin color and background colors. In ourframework, we assume photography in a simple photographic environment where some amateur cameramen take photographs indoors. In such a case, facial skin color is often distorted due to the lighting environment (e.g., light reflected from a colored rear wall), and if the photo is artificially combined with another background, the difference in color is emphasized, resulting in an unnatural synthesized result. In our technique, after roughly extracting the facial region and rectifying the distribution of the skin color in a color space, we perform correction of the color and brightness near the face of the original image so that it matches the color balance ofthefacial image after the color correction. Unlike conventional algorithms for color correction, the final result is attained by a correction process with a guide image. We show through experimental results that more natural results are obtained than conventional methods.