• Proceedings of the Korean Information Science Society Conference
• /
• 2000.04b
• /
• pp.432-434
• /
• 2000

본 논문은 IJG(Independent JPEG Group) JPEG 부호기의 처리 과정중 color table 과 context 버퍼를 이용한 color conversion과 downsampling 방법에 대해 소개한다. IJG JPEG은 전처리 과정에서 context buffer 사용함으로써 각 컴포넌트(RGB)에 대한 color conversion과 downsampling을 효과적으로 수행한다. 또한 각 컴포넌트(RGB)에 대한 부동 소수점 연산의 처리 결과를 미리 계산하여 color table에 저장함으로써 color converter에서 이를 참조, 색차 변환 계산에 적용하도록 하여 처리 속도를 향상 시키고 있다. 이에 본 논문에서는 IJG JPEG의 부호화 과정에서 사용되는 context 버퍼의 구조와 필요성 그리고 color table의 구조와 효과에 대하여 소개한다.

• ETRI Journal
• /
• v.29 no.1
• /
• pp.18-26
• /
• 2007

This paper presents an improved redundant picture coding method that efficiently enhances the error resiliency of H.264. The proposed method applies polyphase downsampling to residual blocks obtained from inter prediction and selectively encodes the rearranged residual blocks in the redundant picture coding process. Moreover, a spatial-temporal sample construction method is developed for the redundant coded picture, which further improves the reconstructed picture quality in error prone environments. Simulations based on JM11.0 were run to verify the proposed method on different test sequences in various error prone environments with average packet loss rates of 3%, 5%, 10%, and 20%. Results of the simulations show that the presented method significantly improves the robustness of H.264 to packet loss by 1.6 dB PSNR on average over the conventional redundant picture coding method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2022.11a
• /
• pp.4-7
• /
• 2022

기존 합성곱 신경망 기반의 잡음 제거 네트워크들은 학습을 위한 noisy-clean 데이터 쌍을 필요로 한다. 하지만 실제 카메라 잡음의 경우, 잡음에 대한 깨끗한 원본 영상을 얻는 것은 불가능하거나 많은 비용이 소모된다. 따라서 이러한 방법을 해결하기 위하여 원본 영상 없이 잡음 영상만으로만 잡음 제거 네트워크를 학습하는 방법들이 제안되어왔다. 그 중 카메라 잡음 영상을 처리하기 위한 대표적인 방법으로 학습과 추론에서 비대칭적인 downsampling을 사용하는 AP-BSN이 제안되었다. 본 논문에서는 Functional neural network를 AP-BSN 알고리즘에 적용하여 다양한 downsampling ratio에 대응되는 하나의 네트워크를 학습하였다. 이를 통해 기존 hyperparameter로 사용되던 downsampling ratio에 대한 결과를 하나의 네트워크에서 분석 및 확인하였다. 또한 해당 파라미터를 조절함으로써 다양한 잡음 제거 후보들을 추출하고 사용자가 원하는 잡음 제거 정도를 조정할 수 있도록 하였다.

• Journal of KIISE:Software and Applications
• /
• v.30 no.7_8
• /
• pp.687-695
• /
• 2003

In this paper, we present a document image compression system based on segmentation, Quincunx downsampling, (5/3) wavelet lifting and subband-oriented SPIHT coding. We reduced the coding time by the adaptation of subband-oriented SPIHT coding and Quincunx downsampling. And to increase compression rate further, we applied arithmetic coding to the bitstream of SPIHT coding output. Finally, we present the reconstructed images for visual comparison and also present the compression rates and PSNR values under various scalar quantization methods.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.42 no.1
• /
• pp.46-49
• /
• 2017

In this letter, we investigate the impact of image downsampling on the performance of background subtraction in Full-HD soccer videos. To this end, we evaluated the performance of background subtraction in terms of both accuracy and computational time. Furthermore, for the sake of completeness, we used two different background subtraction methods under the same experimental setup. For the quantitative comparison, we employed the F-measure and FPS(frames per second). We believe that this study serves as a practically useful benchmark for researchers and practitioners in developing a fast background subtraction algorithm adopted for building real-time intelligent soccer video analysis systems.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.12
• /
• pp.4326-4344
• /
• 2021

The SinGAN is one of generative adversarial networks that can be trained on a single nature image. It has poor ability to learn more global features from nature image, and losses much local detail information when it generates arbitrary size image sample. To solve the problem, a non-linear function is firstly proposed to control downsampling ratio that is ratio between the size of current image and the size of next downsampled image, to increase the ratio with increase of the number of downsampling. This makes the low-resolution images obtained by downsampling have higher proportion in all downsampled images. The low-resolution images usually contain much global information. Therefore, it can help the model to learn more global feature information from downsampled images. Secondly, the attention mechanism is introduced to the generative network to increase the weight of effective image information. This can make the network learn more local details. Besides, in order to make the output image more natural, the TVLoss function is introduced to the loss function of SinGAN, to reduce the difference between adjacent pixels and smear phenomenon for the output image. A large number of experimental results show that our proposed model has better performance than other methods in generating random samples with fixed size and arbitrary size, image harmonization and editing.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2020.06a
• /
• pp.40-41
• /
• 2020

As the capacity of the 3d scanner developed, the reverse engineering using the 3d scanner is emphasized in the construction industry to obtain the 3d geometric representation of buildings. However, big size of the indoor point cloud data acquired by the 3d scanner restricts the efficient process in the reverse engineering. In order to solve this inefficiency, several pre-processing methods simplifying and denoising the raw point cloud data by the rough standard are developed, but these non-standard methods can cause the inaccurate recognition and removal the key-points. This paper analyzes the correlation between the accuracy of wall recognition and the density of the data, thus proposes the proper method for the raw point cloud data. The result of this study could improve the efficiency of the data processing phase in the reverse engineering for indoor point cloud data.

• Journal of Broadcast Engineering
• /
• v.8 no.1
• /
• pp.30-36
• /
• 2003

According to an evolution of image and video compression technologies, most digital images are in the compressed form. Resizing of these compressed images have various applications such as transmission of resized image according to varying bandwidth, content adaptation for display purpose and etc. Discrete Cosine Transform (DCT) is the most popular transformation for image compression. Recently, several researches have been performed to obtain the reconstructed image of original size in the DCT domain after downsampling and upsampling in the DCT domain. Main focus of these researches is to improve quality of the reconstructed image after downsampling and upsampling in the DCT domain In this paper, we present an modified IDCT method to downsize DCT-encoded image. Furthermore, we propose an efficient scheme for image downsampling and upsampling in the DCT domain With these modified IDCT method. The proposed scheme Provides higher PSNR values than the existing schemes In terms of the reconstructed image after halving and doubling in the DCT domain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.465-469
• /
• 2017

In this paper we propose a human body tracking method for application of smartphones. The conventional human body tracking method is divided into a sensor-based method and a vision-based method. The sensor-based methods have a weakness in that tracking accuracy is low due to cumulative error of position information. The vision-based method has no cumulative error, but it requires reduction of the computational complexity for application of smartphone. In this paper we use the improved HOG algorithm as a human body tracking method for application of smartphone. The improved HOG algorithm is implemented through downsampling and frame sampling. Gaussian pyramid is applied for downsampling, and uniform sampling is applied for frame sampling. We measured the proposed algorithm on two devices, four resolutions, and four frame sampling intervals. We derive the best detection rate among downsampling and frame sampling parameters that can be applied in realtime.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.8
• /
• pp.1714-1719
• /
• 2011

High quality image processing schemes are used more widely than ever according to the development of various visual media. We need a compressed form of image for sending more capacity and a controlling strategy of images for small display devices. In this paper, we propose an image upsampling and downsamplig scheme using DCT coefficients for those purposes. Our scheme is designed to control the size of picture based on the target display media by reducing the data in DCT domain while not increasing the computational burdens. With the power of controlling the resolution in DCT domain, the proposed method shows higher PSNR than other competing methods in experiment.