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Showing papers on "Image scaling published in 2007"


Journal ArticleDOI
TL;DR: This paper adapt and expand kernel regression ideas for use in image denoising, upscaling, interpolation, fusion, and more and establishes key relationships with some popular existing methods and shows how several of these algorithms are special cases of the proposed framework.
Abstract: In this paper, we make contact with the field of nonparametric statistics and present a development and generalization of tools and results for use in image processing and reconstruction. In particular, we adapt and expand kernel regression ideas for use in image denoising, upscaling, interpolation, fusion, and more. Furthermore, we establish key relationships with some popular existing methods and show how several of these algorithms, including the recently popularized bilateral filter, are special cases of the proposed framework. The resulting algorithms and analyses are amply illustrated with practical examples

1,457 citations


Journal ArticleDOI
TL;DR: The proposed technique would also allow precise coregistration of images for the measurement of surface displacements due to ice-flow or geomorphic processes, or for any other change detection applications.
Abstract: We describe a procedure to accurately measure ground deformations from optical satellite images. Precise orthorectification is obtained owing to an optimized model of the imaging system, where look directions are linearly corrected to compensate for attitude drifts, and sensor orientation uncertainties are accounted for. We introduce a new computation of the inverse projection matrices for which a rigorous resampling is proposed. The irregular resampling problem is explicitly addressed to avoid introducing aliasing in the ortho-rectified images. Image registration and correlation is achieved with a new iterative unbiased processor that estimates the phase plane in the Fourier domain for subpixel shift detection. Without using supplementary data, raw images are wrapped onto the digital elevation model and coregistered with a 1/50 pixel accuracy. The procedure applies to images from any pushbroom imaging system. We analyze its performance using Satellite pour l'Observation de la Terre (SPOT) images in the case of a null test (no coseismic deformation) and in the case of large coseismic deformations due to the Mw 7.1 Hector Mine, California, earthquake of 1999. The proposed technique would also allow precise coregistration of images for the measurement of surface displacements due to ice-flow or geomorphic processes, or for any other change detection applications. A complete software package, the Coregistration of Optically Sensed Images and Correlation, is available for download from the Caltech Tectonics Observatory website

777 citations


Proceedings ArticleDOI
29 Jul 2007
TL;DR: A new method for upsampling images which is capable of generating sharp edges with reduced input-resolution grid-related artifacts, based on a statistical edge dependency relating certain edge features of two different resolutions, which is generically exhibited by real-world images.
Abstract: In this paper we propose a new method for upsampling images which is capable of generating sharp edges with reduced input-resolution grid-related artifacts. The method is based on a statistical edge dependency relating certain edge features of two different resolutions, which is generically exhibited by real-world images. While other solutions assume some form of smoothness, we rely on this distinctive edge dependency as our prior knowledge in order to increase image resolution. In addition to this relation we require that intensities are conserved; the output image must be identical to the input image when downsampled to the original resolution. Altogether the method consists of solving a constrained optimization problem, attempting to impose the correct edge relation and conserve local intensities with respect to the low-resolution input image. Results demonstrate the visual importance of having such edge features properly matched, and the method's capability to produce images in which sharp edges are successfully reconstructed.

480 citations


Journal ArticleDOI
TL;DR: In this article, a new method for upsampling images which is capable of generating sharp edges with reduced input-resolution grid-related artifacts is proposed, which is based on a statistical edg...
Abstract: In this paper we propose a new method for upsampling images which is capable of generating sharp edges with reduced input-resolution grid-related artifacts. The method is based on a statistical edg...

224 citations


Proceedings ArticleDOI
17 Jun 2007
TL;DR: Unlike previous approaches to the same problem, intensity blending as well as image resampling are avoided on all stages of the process, which ensures that the resolution of the produced texture is essentially the same as that of the original views.
Abstract: Image-based object modeling has emerged as an important computer vision application. Typically, the process starts with the acquisition of the image views of an object. These views are registered within the global coordinate system using structure-and-motion techniques, while on the next step the geometric shape of an object is recovered using stereo and/or silhouette cues. This paper considers the final step, which creates the texture map for the recovered geometry model. The approach proposed in the paper naturally starts by backprojecting original views onto the obtained surface. A texture is then mosaiced from these back projections, whereas the quality of the mosaic is maximized within the process of Markov random field energy optimization. Finally, the residual seams between the mosaic components are removed via seam levelling procedure, which is similar to gradient-domain stitching techniques recently proposed for image editing. Unlike previous approaches to the same problem, intensity blending as well as image resampling are avoided on all stages of the process, which ensures that the resolution of the produced texture is essentially the same as that of the original views. Importantly, due to restriction to non-greedy energy optimization techniques, good results are produced even in the presence of significant errors on image registration and geometric estimation steps.

220 citations


Journal ArticleDOI
TL;DR: In this paper, it is shown that the interpolation has a smoothing effect which depends of the applied shift. And a strategy to attenuate the interpolations artifacts is proposed to increase the quality of the similarity estimation.
Abstract: Subpixel accuracy image registration is needed for applications such as digital elevation model extraction, change detection, pan-sharpening, and data fusion. In order to achieve this accuracy, the deformation between the two images to be registered is usually modeled by a displacement vector field which can be estimated by measuring rigid local shifts for each pixel in the image. In order to measure subpixel shifts, one uses image resampling. Sampling theory says that, if a continuous signal has been sampled according to the Nyquist criterion, a perfect continuous reconstruction can be obtained from the sampled version. Therefore, a shifted version of a sampled signal can be obtained by interpolation and resampling with a shifted origin. Since only a sampled version of the shifted signal is needed, the reconstruction needs only to be performed for the new positions of the samples, so the whole procedure comes to computing the value of the signal for the new sample positions. In the case of image registration, the similarity between the reference image and the shifted versions of the image to be registered is measured, assuming that the maximum of similarity determines the most likely shift. The image interpolation step is thus performed a high number of times during the similarity optimization procedure. In order to reduce the computation cost, approximate interpolations are performed. Approximate interpolators will introduce errors in the resampled image which may induce errors in the similarity measure and therefore produce errors in the estimated shifts. In this paper, it is shown that the interpolation has a smoothing effect which depends of the applied shift. This means that, in the case of noisy images, the interpolation has a denoising effect, and therefore, it increases the quality of the similarity estimation. Since this blurring is not the same for every shift, the similarity may be low for a null shift (no blurring) and higher for shifts close to half a pixel (strong blurring). This paper presents an analysis of the behavior of the different interpolators and their effects on the similarity measures. This analysis will be done for the two similarity measures: the correlation coefficient and the mutual information. Finally, a strategy to attenuate the interpolation artifacts is proposed

97 citations


Journal ArticleDOI
TL;DR: A new class of image morphing algorithms is proposed based on the theory of optimal mass transport, which is an intensity-based approach and, thus, is parameter free.
Abstract: Image morphing, or image interpolation in the time domain, deals with the metamorphosis of one image into another. In this paper, a new class of image morphing algorithms is proposed based on the theory of optimal mass transport. The L2 mass moving energy functional is modified by adding an intensity penalizing term, in order to reduce the undesired double exposure effect. It is an intensity-based approach and, thus, is parameter free. The optimal warping function is computed using an iterative gradient descent approach. This proposed morphing method is also extended to doubly connected domains using a harmonic parameterization technique, along with finite-element methods

82 citations


Journal ArticleDOI
TL;DR: This paper introduces an experimental framework for the computational pickup process and the CIIR process using a Gaussian function, and carries out experiments on real objects to subjectively evaluate the proposed method.
Abstract: In this paper, we propose a computational integral imaging reconstruction (CIIR) method by use of image interpolation algorithms to improve the visual quality of 3D reconstructed images. We investigate the characteristics of the conventional CIIR method along the distance between lenslet and objects. What we observe is that the visual quality of reconstructed images is periodically degraded. The experimentally observed period is half size of the elemental image. To remedy this problem, we focus on the interpolation methods in computational integral imaging. Several interpolation methods are applied to the conventional CIIR method and their performances are analyzed. To objectively evaluate the proposed CIIR method, we introduce an experimental framework for the computational pickup process and the CIIR process using a Gaussian function. We also carry out experiments on real objects to subjectively evaluate the proposed method. Experimental results indicate that our method outperforms the conventional CIIR method. In addition, our method reduces the grid noise that the conventional CIIR method suffers from.

79 citations


Proceedings ArticleDOI
TL;DR: A novel image interpolation algorithm that uses the new contourlet transform to improve the regularity of object boundaries in the generated images and significantly outperforms linear interpolation in subjective quality and in most cases, in terms of PSNR as well.
Abstract: With the ever increasing computational power of modern day processors, it has become feasible to use more robust and computationally complex algorithms that increase the resolution of images without distorting edges and contours. We present a novel image interpolation algorithm that uses the new contourlet transform to improve the regularity of object boundaries in the generated images. By using a simple wavelet-based linear interpolation scheme as our initial estimate, we use an iterative projection process based on two constraints to drive our solution towards an improved high-resolution image. Our experimental results show that our new algorithm significantly outperforms linear interpolation in subjective quality, and in most cases, in terms of PSNR as well.

77 citations


Journal ArticleDOI
01 Oct 2007-Ubiquity
TL;DR: The underlying computational foundations of all these algorithms and their implementation techniques are described and some experimental results are presented to show the impact of these algorithms in terms of image quality metrics and computational requirements for implementation.
Abstract: Image interpolation is an important image processing operation applied in diverse areas ranging from computer graphics, rendering, editing, medical image reconstruction, to online image viewing. Image interpolation techniques are referred in literature by many terminologies, such as image resizing, image resampling, digital zooming, image magnification or enhancement, etc. Basically, an image interpolation algorithm is used to convert an image from one resolution (dimension) to another resolution without loosing the visual content in the picture. Image interpolation algorithms can be grouped in two categories, non-adaptive and adaptive. The computational logic of an adaptive image interpolation technique is mostly dependent upon the intrinsic image features and contents of the input image whereas computational logic of a non-adaptive image interpolation technique is fixed irrespective of the input image features. In this paper, we review the progress of both non-adaptive and adaptive image interpolation techniques. We also proposed a new algorithm for image interpolation in discrete wavelet transform domain and shown its efficacy. We describe the underlying computational foundations of all these algorithms and their implementation techniques. We present some experimental results to show the impact of these algorithms in terms of image quality metrics and computational requirements for implementation.

73 citations


Patent
24 Jul 2007
TL;DR: In this paper, the interpolation control module adjusts the frame interpolation operation in response to the analysis of the information associated with one or more frames, in order to select a different type of interpolation, select a video frame prediction mode, or select different threshold values for frame interpolations.
Abstract: In general, this disclosure is directed to decoding techniques for interpolating video frames. In particular, the techniques of this disclosure may be used to dynamically adjust a frame interpolation operation based on analysis of information associated with one or more video frames. In response to the analysis of the information associated with one or more frames, the interpolation control module adjusts the frame interpolation operation in number of different manners. For example, the interpolation control module may dynamically enable or disable motion compensated frame interpolation, select a different type of interpolation, select a video frame prediction mode to be used in the motion compensated frame interpolation, or select different threshold values for frame interpolation.

Journal ArticleDOI
TL;DR: A new heterogeneity-projection scheme based on a novel spectral-spatial correlation concept is proposed to estimate the best interpolation direction directly from the original mosaic image and perform hard-decision interpolation, in which each pixel only needs to be interpolated once.
Abstract: This paper presents a novel heterogeneity-projection hard-decision (HPHD) color interpolation procedure for reproduction of Bayer mosaic images. The proposed algorithm aims to estimate the optimal interpolation direction and perform hard-decision interpolation, in which each pixel only needs to be interpolated once. A new heterogeneity-projection scheme based on a novel spectral-spatial correlation concept is proposed to estimate the best interpolation direction directly from the original mosaic image. Using the proposed heterogeneity-projection scheme, a hard-decision rule can be decided before performing the interpolation. The advantage of this scheme is that it provides an efficient way for decision-based algorithms to generate improved results using fewer computations. Compared with three recently reported demosaicing techniques, Gunturk's, Lu's, and Li's methods, the proposed HPHD outperforms all of them in both PSNR values and S-CIELAB DeltaEab * measures by utilizing 25 natural images from Kodak PhotoCD

Journal IssueDOI
TL;DR: Although this interpolation method does not restore the original image, the authors confirmed through experimental results that it can provide interpolation without a feeling of oddness for images which have a high level of self-correlation.
Abstract: In this paper the authors propose a method to use interpolation to eliminate characters in only one image with telops or other text through an image interpolation method that uses the eigenspace method. Background scenes and other images have a fractal character, and often the self-correlation in the image can be assumed to be high. The authors focus on this point and represent rules for describing the image based on an eigenspace consisting of only one image that has defects. The eigenspace generated in this manner reflects the features of the image, and by using this eigenspace, image interpolation can be achieved. Although this interpolation method does not restore the original image, the authors confirmed through experimental results that it can provide interpolation without a feeling of oddness for images which have a high level of self-correlation. © 2006 Wiley Periodicals, Inc. Syst Comp Jpn, 38(1): 87– 96, 2007; Published online in Wiley InterScience (). DOI 10.1002sscj.10319.

Journal ArticleDOI
TL;DR: New reconstruction methods for hexagonally sampled data are proposed that use the intrinsically 2-D nature of the lattice, and that at the same time remain practical and efficient, and rely on the quasi-interpolation paradigm to design compelling prefilters.
Abstract: The reconstruction of a continuous-domain representation from sampled data is an essential element of many image processing tasks, in particular, image resampling. Until today, most image data have been available on Cartesian lattices, despite the many theoretical advantages of hexagonal sampling. In this paper, we propose new reconstruction methods for hexagonally sampled data that use the intrinsically 2-D nature of the lattice, and that at the same time remain practical and efficient. To that aim, we deploy box-spline and hex-spline models, which are notably well adapted to hexagonal lattices. We also rely on the quasi-interpolation paradigm to design compelling prefilters; that is, the optimal filter for a prescribed design is found using recent results from approximation theory. The feasibility and efficiency of the proposed methods are illustrated and compared for a hexagonal to Cartesian grid conversion problem

Patent
18 Sep 2007
TL;DR: In this paper, a method for real-time video transmission over networks with varying bandwidth is described, where image quality is maintained even under degrading network performance conditions through the use of image scaling in conjunction with block based motion compensated video coding (MPEG2/4, H.264, et al.).
Abstract: A method for real time video transmission over networks with varying bandwidth is described. Image quality is maintained even under degrading network performance conditions through the use of image scaling in conjunction with block based motion compensated video coding (MPEG2/4, H.264, et. Al.). The ability to quickly switch resolutions without decreasing reference frame correlation is shown enabling a fast switch to reduce the required bandwidth for stable image quality.

Journal ArticleDOI
TL;DR: A novel edge-adaptive demosaicing algorithm (EADA) is proposed in this paper to effectively reduce color artifacts in demosaiced images from a color filter array (CFA) by exploiting high-frequency information of the green channel.

Journal ArticleDOI
TL;DR: Simulation results demonstrate that the proposed new resolution enhancement algorithm can produce a higher visual quality for the interpolated image than the conventional interpolation methods.
Abstract: In this paper, a novel human visual system (HVS)-directed neural-network-based adaptive interpolation scheme for natural image is proposed. A fuzzy decision system built from the characteristics of the HVS is proposed to classify pixels of the input image into human perception nonsensitive class and sensitive class. Bilinear interpolation is used to interpolate the nonsensitive regions and a neural network is proposed to interpolate the sensitive regions along edge directions. High-resolution digital images along with supervised learning algorithms are used to automatically train the proposed neural network. Simulation results demonstrate that the proposed new resolution enhancement algorithm can produce a higher visual quality for the interpolated image than the conventional interpolation methods.

Journal ArticleDOI
01 Oct 2007-Ubiquity
TL;DR: Image interpolation is an important image processing operation applied in diverse areas ranging from computer graphics, rendering, editing, medical image reconstruction, to online image viewing.
Abstract: Image interpolation is an important image processing operation applied in diverse areas ranging from computer graphics, rendering, editing, medical image reconstruction, to online image viewing. Im...

Proceedings ArticleDOI
TL;DR: A new algorithm is presented that performs demosaicing and super-resolution jointly from a set of raw images sampled with a color filter array using normalized convolution, an image interpolation method from a nonuniform set of samples.
Abstract: We present a new algorithm that performs demosaicing and super-resolution jointly from a set of raw images sampled with a color filter array. Such a combined approach allows us to compute the alignment parameters between the images on the raw camera data before interpolation artifacts are introduced. After image registration, a high resolution color image is reconstructed at once using the full set of images. For this, we use normalized convolution, an image interpolation method from a nonuniform set of samples. Our algorithm is tested and compared to other approaches in simulations and practical experiments.

Journal ArticleDOI
TL;DR: An alias removal technique by designing an alias-free upsampling scheme is proposed by minimizing the total variation of the interpolant subject to the constraint that part of alias free spectral components in the low resolution observation are known precisely and under the assumption of sparsity in the data.
Abstract: In this paper we study the usefulness of different local and global, learning-based, single-frame image super-resolution reconstruction techniques in handling three specific tasks, namely, de-blurring, de-noising and alias removal. We start with the global, iterative Papoulis---Gerchberg method for super-resolving a scene. Next we describe a PCA-based global method which faithfully reproduces a super-resolved image from a blurred and noisy low resolution input. We also study several multi-resolution processing schemes for super-resolution where the best edges are learned locally from an image database. We show that the PCA-based global method is efficient in handling blur and noise in the data. The local methods are adept in capturing the edges properly. However, both local and global approaches cannot properly handle the aliasing present in the low resolution observation. Hence we propose an alias removal technique by designing an alias-free upsampling scheme. Here the unknown high frequency components of the given partially aliased (low resolution) image is generated by minimizing the total variation of the interpolant subject to the constraint that part of alias free spectral components in the low resolution observation are known precisely and under the assumption of sparsity in the data.

Book ChapterDOI
10 Jun 2007
TL;DR: This work proposes a GPU-friendly algorithm for image up-sampling by edge-directed image interpolation, which avoids ringing artifacts, excessive blurring, and staircasing of oblique edges, and allows for real-time processing of full-screen images on today's GPUs.
Abstract: The rendering of lower resolution image data on higher resolution displays has become a very common task, in particular because of the increasing popularity of webcams, camera phones, and low-bandwidth video streaming. Thus, there is a strong demand for real-time, high-quality image magnification. In this work, we suggest to exploit the high performance of programmable graphics processing units (GPUs) for an adaptive image magnification method. To this end, we propose a GPU-friendly algorithm for image up-sampling by edge-directed image interpolation, which avoids ringing artifacts, excessive blurring, and staircasing of oblique edges. At the same time it features gray-scale invariance, is applicable to color images, and allows for real-time processing of full-screen images on today's GPUs.

Proceedings ArticleDOI
29 Aug 2007
TL;DR: This work analytically describes specific periodic properties presence in interpolated signals and their derivatives and proposes an efficient and blind method to automatically detect the traces of geometric transformations in images and their portions.
Abstract: In our society digital images are a powerful and widely used communication medium. They have an important impact on our life. In recent years, due to the advent of high-performance consumer hardware and improved human computer interfaces, it has become relatively easy to create fake images. Typically, to create high quality and consistent forgeries, several types of tampering techniques are employed simultaneously. One of the most often used techniques is resampling (especially when two or more images are spliced together). Generally, resampling is based on an interpolation procedure. Typically, this procedure brings into the signal specific statistical changes. In this work we analyze and analytically describe specific periodic properties presence in interpolated signals and their derivatives. Furthermore, we propose an efficient and blind method to automatically detect the traces of geometric transformations in images and their portions. The results of the proposed method are demonstrated on several examples.

Journal ArticleDOI
TL;DR: The proposed bicubic method adopts both the local asymmetry features and the local gradient features of an image in the interpolation processing to obtain high accuracy interpolated images.
Abstract: In this paper, we propose a novel bicubic method for digital image interpolation. Since the conventional bicubic method does not consider image local features, the interpolated images obtained by the conventional bicubic method often have a blurring problem. In this paper, the proposed bicubic method adopts both the local asymmetry features and the local gradient features of an image in the interpolation processing. Experimental results show that the proposed method can obtain high accuracy interpolated images.

Proceedings ArticleDOI
07 Mar 2007
TL;DR: A discrete wavelet transform (DWT) based digital image watermarking technique, which considers the watermark signal as a binary sequence which is embedded to the high frequency band of the blue channel.
Abstract: We propose in this paper a discrete wavelet transform (DWT) based digital image watermarking technique. For embedding process, we consider the watermark signal as a binary sequence which is embedded to the high (HL and HH) frequency band of the blue channel. For detecting process, the correlation between the high frequency band DWT coefficients of the watermarked image and the watermark signal is compared with the predefined threshold to determine whether the watermark is present or not. The experimental results show that the method is comparatively robust to several attacks such as rotation, scaling, JPEG compression, cropping, and multiple watermarking.

Proceedings ArticleDOI
12 Nov 2007
TL;DR: This paper proposed an approach to deal with the problem during generating of LDI, which refines colors of the depth pixels by choosing proper candidate depth pixels, removes matting effects by projecting LDI backward to reference views, and eliminates the gaps or holes due to disocclusion and undersample by local background interpolation.
Abstract: The feature of rendering arbitrary view make layered depth image (LDI) be suitable to present multi-view video data and provide interactivity form such as free view video(FVV). However, visual artifacts occurred in the rendered result limit the practicality of LDI. In this paper, we proposed an approach to deal with this problem during generating of LDI, which refines colors of the depth pixels by choosing proper candidate depth pixels, removes matting effects by projecting LDI backward to reference views, and eliminate the gaps or holes due to disocclusion and undersample by local background interpolation. Experimental results show that our approach is practicable and efficient.

Patent
28 Nov 2007
TL;DR: In this article, a multi-bit digital watermark method against the print scanning and the geometric transformation is presented, which comprises the following steps: embedding the watermark in dispersion Fourier amplitude coefficient of the image, determining which Fourier coefficient every watermark bit embeds in according to the dispersion logarithmic polar coordinate of the Fourier coefficients, making the watermarks detecting and extracting out-of-step when the image is carried out the geometric transformations of the pantographic rotating or the print scan scanning, and synchronizing the information watermark according to
Abstract: The invention discloses a multi-bit digital watermark method against the print scanning and the geometric transformation, which comprises the following steps: embedding the watermark in dispersion Fourier amplitude coefficient of the image; determining which Fourier amplitude coefficient every watermark bit embeds in according to the dispersion logarithmic polar coordinate of the Fourier amplitude coefficient; making the watermark detecting and extracting out-of-step when the image is carried out the geometric transformation of the pantographic rotating or the print scanning; synchronizing the information watermark according to the relation of the original mode and embedded mold when the watermark is detected and extracted because the pantograph and the rotating of the image corresponds with the translation of the Fourier logarithmic polar coordinate field at the radial and angel direction; extracting the meaning watermark information bit string; introducing the real interpolation and saving the time because the watermark embedding and detecting process doesn' t need the image interpolation arithmetic for the image and the Fourier amplitude coefficient; protecting the embedded mode. The invention can apply to the copyright protection of the digital image and video, false proof of the file and evidence, the monitoring of video broadcast.

Proceedings ArticleDOI
TL;DR: Algorithms for the resizing of images based on the analysis of the sum of primary implicants representation of image data, as generated by a logical transform are presented.
Abstract: The resizing of data, either upscaling or downscaling based on need for increased or decreased resolution, is an important signal processing technique due to the variety of data sources and formats used in today's world. Image interpolation, the 2D variation, is commonly achieved through one of three techniques: nearest neighbor, bilinear interpolation, or bicubic interpolation. Each method comes with advantages and disadvantages and selection of the appropriate one is dependent on output and situation specifications. Presented in this paper are algorithms for the resizing of images based on the analysis of the sum of primary implicants representation of image data, as generated by a logical transform. The most basic algorithm emulates the nearest neighbor technique, while subsequent variations build on this to provide more accuracy and output comparable to the other traditional methods. Computer simulations demonstrate the effectiveness of these algorithms on binary and grayscale images.

Journal Article
TL;DR: The results show that compari- son of image interpolation methods depends on down- scaling technique, image contents and quality metric, and for fair comparison all these parameters need to be considered.
Abstract: Discrete wavelet transform (DWT) can be used in various applications, such as image compression and coding. In this paper we examine how DWT can be used in image interpolation. Afterwards proposed method is com- pared with two other traditional interpolation methods. For the case of magnified image achieved by interpolation, original image is unknown and there is no perfect way to judge the magnification quality. Common approach is to start with an original image, generate a lower resolution version of original image by downscaling, and then use different interpolation methods to magnify low resolution image. After that original and magnified images are com- pared to evaluate difference between them using different picture quality measures. Our results show that compari- son of image interpolation methods depends on down- scaling technique, image contents and quality metric. For fair comparison all these parameters need to be considered.

Patent
27 Jul 2007
TL;DR: In this article, a linear pixel clock is used to determine the position of a pixel in a 2D image, and displayed pixel intensities are determined using interpolation techniques, where nonlinear image scan trajectories such as sinusoidal and bi-sinusoidal trajectories are accommodated.
Abstract: An image generation apparatus provides interpolation and distortion correction. The interpolation and distortion correction may be provided in one or two dimensions. Nonlinear image scan trajectories, such as sinusoidal and bi-sinusoidal trajectories are accommodated. Horizontal and vertical scan positions are determined using a linear pixel clock, and displayed pixel intensities are determined using interpolation techniques.

Journal ArticleDOI
TL;DR: In this article, a low complexity motion compensated frame interpolation method using compressed-domain information based on an H.264 decoder is presented, where the motion vectors are estimated using the constant acceleration motion model, and the interpolation algorithm is applied based on the macroblock coded types.
Abstract: A low complexity motion compensated frame interpolation method using compressed-domain information based on an H.264 decoder is presented. In the proposed method, the motion vectors are estimated using the constant acceleration motion model, and the interpolation algorithm is applied based on the macroblock coded types. Results show that the proposed method provides high quality interpolation frames.