• Title/Summary/Keyword: upsampling

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Hardware-Saving Realizations of Interpolators and Decimators Using Periodically Time-Varying Coefficients

  • Ratansanya, San;Amornraksa, Thumrongrat;Tipakorn, Bundit
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.860-863
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    • 2002
  • Realizations of multirate converters are proposed using periodically time-varying (PTV) structures. By exploiting the computational redundancy of the filtering operation in a multirate filter, it is possible to implement the filter with much less hardware. In the proposed implementations, several coefficients time-share in a periodic fashion the hardware of one multiply-and-add. Therefore, each multiply-and-add circuit performs different coefficient scalings at different time instants within a period. Compared to the direct form realization, the proposed realizations reduce the hardware of an interpolator and a decimator by a factor of approximately U and M, respectively, while retaining the same processing speed, where U and M are the upsampling and downsampling factors, respectively. The approach can be used to obtain realizations for sampling rate conversion by a rational factor of U/M, where U and M are relatively prime, in which case hardware reduction by a factor of approximately UM can be achieved.

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Depth Up-Sampling via Pixel-Classifying and Joint Bilateral Filtering

  • Ren, Yannan;Liu, Ju;Yuan, Hui;Xiao, Yifan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3217-3238
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    • 2018
  • In this paper, a depth image up-sampling method is put forward by using pixel classifying and jointed bilateral filtering. By analyzing the edge maps originated from the high-resolution color image and low-resolution depth map respectively, pixels in up-sampled depth maps can be classified into four categories: edge points, edge-neighbor points, texture points and smooth points. First, joint bilateral up-sampling (JBU) method is used to generate an initial up-sampling depth image. Then, for each pixel category, different refinement methods are employed to modify the initial up-sampling depth image. Experimental results show that the proposed algorithm can reduce the blurring artifact with lower bad pixel rate (BPR).

Sports Video Position Retrival System Using Frame Merging (프레임 병합을 이용한 스포츠 동영상 위치 검색 시스템)

  • 이지현;임정훈;이양원
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2002.11a
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    • pp.619-623
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    • 2002
  • We can speak caption as information that can not except caption on sports video. The sports highlight were composed that we recognize captioning. This paper is the necessary work to the middle-step to analysis the caption through the retrieval and discrimination from the position of caption. This paper improve at first and simplify the image through the excellent threshold value algorithm in the preprocessing and then use method that can analysis caption through the multiplex frame merging algorithm. Its speed performing shows up higher and simplier than the region growing process.

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Super-Resolution Image Processing Algorithm Using Hybrid Up-sampling (하이브리드 업샘플링을 이용한 베이시안 초해상도 영상처리)

  • Park, Jong-Hyun;Kang, Moon-Gi
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.109-110
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    • 2007
  • 본 논문에서는 베이시안 초해상도 영상처리시 저해상도 영상들을 고해상도 격자에 맞게 정합해서 업샘플링(upsampling)을 하는 새로운 방식에 대해 제안한다. 제안하는 업샘플링 방식은 각 장을 따로 보간하는 방식과 달리 여러 저해상도 영상의 고주파 정보가 고해상도 영상 격자의 모든 위치에 적절히 영향을 미칠 수 있도록 여러 장의 저해상도 영상의 고주파 정보를 함께 사용하여 보간한다. 보간하는 방법은 B-스플라인 (B-Spline) 기반 비정규 리샘플링(non-uniform resampling)을 기반으로 초해상도 영상처리에 맞도록 적용한다. 실험결과를 통해 일반적으로 적용되는 0-삽입(zero-padding) 업샘플링 방식과 쌍일차 보간법(bilinear interpolation) 등을 적용할 때의 효과를 살펴보고, 제안하는 방식이 일반적인 방식을 사용하는 것에 비해 정량적, 정성적으로 고해상도 정보를 더 정확히 생성해내는 것을 확인한다.

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Deep Adversarial Residual Convolutional Neural Network for Image Generation and Classification

  • Haque, Md Foysal;Kang, Dae-Seong
    • Journal of Advanced Information Technology and Convergence
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    • v.10 no.1
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    • pp.111-120
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    • 2020
  • Generative adversarial networks (GANs) achieved impressive performance on image generation and visual classification applications. However, adversarial networks meet difficulties in combining the generative model and unstable training process. To overcome the problem, we combined the deep residual network with upsampling convolutional layers to construct the generative network. Moreover, the study shows that image generation and classification performance become more prominent when the residual layers include on the generator. The proposed network empirically shows that the ability to generate images with higher visual accuracy provided certain amounts of additional complexity using proper regularization techniques. Experimental evaluation shows that the proposed method is superior to image generation and classification tasks.

Low-clock-speed time-interleaved architecture for a polar delta-sigma modulator transmitter

  • Nasser Erfani Majd;Rezvan Fani
    • ETRI Journal
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    • v.45 no.1
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    • pp.150-162
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    • 2023
  • The polar delta-sigma modulator (DSM) transmitter architecture exhibits good coding efficiency and can be used for software-defined radio applications. However, the necessity of high clock speed is one of the major drawbacks of using this transmitter architecture. This study proposes a low-complexity timeinterleaved architecture for the polar DSM transmitter baseband part to reduce the clock speed requirement of the polar DSM transmitter using an upsampling technique. Simulations show that using the proposed four-branch timeinterleaved polar DSM transmitter baseband part, the clock speed requirement of the transmitter is reduced by four times without degrading the signal-tonoise-and-distortion ratio.

Analysis of Optimal Resolution and Number of GCP Chips for Precision Sensor Modeling Efficiency in Satellite Images (농림위성영상 정밀센서모델링 효율성 재고를 위한 최적의 해상도 및 지상기준점 칩 개수 분석)

  • Choi, Hyeon-Gyeong;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1445-1462
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    • 2022
  • Compact Advanced Satellite 500-4 (CAS500-4), which is scheduled to be launched in 2025, is a mid-resolution satellite with a 5 m resolution developed for wide-area agriculture and forest observation. To utilize satellite images, it is important to establish a precision sensor model and establish accurate geometric information. Previous research reported that a precision sensor model could be automatically established through the process of matching ground control point (GCP) chips and satellite images. Therefore, to improve the geometric accuracy of satellite images, it is necessary to improve the GCP chip matching performance. This paper proposes an improved GCP chip matching scheme for improved precision sensor modeling of mid-resolution satellite images. When using high-resolution GCP chips for matching against mid-resolution satellite images, there are two major issues: handling the resolution difference between GCP chips and satellite images and finding the optimal quantity of GCP chips. To solve these issues, this study compared and analyzed chip matching performances according to various satellite image upsampling factors and various number of chips. RapidEye images with a resolution of 5m were used as mid-resolution satellite images. GCP chips were prepared from aerial orthographic images with a resolution of 0.25 m and satellite orthogonal images with a resolution of 0.5 m. Accuracy analysis was performed using manually extracted reference points. Experiment results show that upsampling factor of two and three significantly improved sensor model accuracy. They also show that the accuracy was maintained with reduced number of GCP chips of around 100. The results of the study confirmed the possibility of applying high-resolution GCP chips for automated precision sensor modeling of mid-resolution satellite images with improved accuracy. It is expected that the results of this study can be used to establish a precise sensor model for CAS500-4.

System Development and IC Implementation of High-quality and High-performance Image Downscaler Using 2-D Phase-correction Digital Filters (2차원 위상 교정 디지털 필터를 이용한 고성능/고화질의 영상 축소기 시스템 개발 및 IC 구현)

  • 강봉순;이영호;이봉근
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.3
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    • pp.93-101
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    • 2001
  • In this paper, we propose an image downscaler used in multimedia video applications, such as DTV, TV-PIP, PC-video, camcorder, videophone and so on. The proposed image downscaler provides a scaled image of high-quality and high-performance. This paper will explain the scaling theory using two-dimensional digital filters. It is the method that removes an aliasing noise and decreases the hardware complexity, compared with Pixel-drop and Upsamling. Also, this paper will prove it improves scaling precisians and decreases the loss of data, compared with the Scaler32, the Bt829 of Brooktree, and the SAA7114H of Philips. The proposed downscaler consists of the following four blocks: line memory, vertical scaler, horizontal scaler, and FIFO memory. In order to reduce the hardware complexity, the using digital filters are implemented by the multiplexer-adder type scheme and their all the coefficients can be simply implemented by using shifters and adders. It also decreases the loss of high frequency data because it provides the wider BW of 6MHz as adding the compensation filter. The proposed downscaler is modeled by using the Verilog-HDL and the model is verified by using the Cadence simulator. After the verification is done, the model is synthesized into gates by using the Synopsys. The synthesized downscaler is Placed and routed by the Mentor with the IDEC-C632 0.65${\mu}{\textrm}{m}$ library for further IC implementation. The IC master is fixed in size by 4,500${\mu}{\textrm}{m}$$\times$4,500${\mu}{\textrm}{m}$. The active layout size of the proposed downscaler is 2,528${\mu}{\textrm}{m}$$\times$3,237${\mu}{\textrm}{m}$.

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Comparison of Objective Metrics and 3D Evaluation Using Upsampled Depth Map (깊이맵 업샘플링을 이용한 객관적 메트릭과 3D 평가의 비교)

  • Mahmoudpour, Saeed;Choi, Changyeol;Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.20 no.2
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    • pp.204-214
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    • 2015
  • Depth map upsampling is an approach to increase the spatial resolution of depth maps obtained from a depth camera. Depth map quality is closely related to 3D perception of stereoscopic image, multi-view image and holography. In general, the performance of upsampled depth map is evaluated by PSNR (Peak Signal to Noise Ratio). On the other hand, time-consuming 3D subjective tests requiring human subjects are carried out for examining the 3D perception as well as visual fatigue for 3D contents. Therefore, if an objective metric is closely correlated with a subjective test, the latter can be replaced by the objective metric. For this, this paper proposes a best metric by investigating the relationship between diverse objective metrics and 3D subjective tests. Diverse reference and no-reference metrics are adopted to evaluate the performance of upsampled depth maps. The subjective test is performed based on DSCQS test. From the utilization and analysis of three kinds of correlations, we validated that SSIM and Edge-PSNR can replace the subjective test.

Fast Multiple-Image-Based Deblurring Method (다중 영상 기반의 고속 처리용 디블러링 기법)

  • Son, Chang-Hwan;Park, Hyung-Min
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.4
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    • pp.49-57
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    • 2012
  • This paper presents a fast multiple-image-based deblurring method that decreases the computation loads in the image deblurring, enhancing the sharpness of the textures or edges of the restored images. First, two blurred images with some blurring artifacts and one noisy image including severe noises are consecutively captured under a relatively long and short exposures, respectively. To improve the processing speeds, the captured multiple images are downsampled at the ratio of two, and then a way of estimating the point spread function(PSF) based on the image or edge patches extracted from the whole images, is introduced. The method enables to effectively reduce the computation time taken in the PSF prediction. Next, the texture-enhanced image deblurring method of supplementing the ability of the texture representation degraded by the downsampling of the input images, is developed and then applied. Finally, to get the same image size as the original input images, an upsampling method of utilizing the sharp edges of the captured noisy image is applied. By using the proposed method, the processing times taken in the image deblurring, which is the main obstacle of its application to the digital cameras, can be shortened, while recovering the fine details of the textures or edge components.