Chae-Eun Lee

To reduce the size and bandwidth requirement of a frame memory for video compression, a number of memory recompression algorithms have been proposed. These previous algorithms are performed independently of a video compression standard and therefore do not take advantage of the information obtained during the processing of the compression standard. This paper proposes a new recompression algorithm that makes use of the information from H.264 intra prediction results. The proposed algorithm decom

In this paper, we investigate the core-switch mapping (CSM) problem that optimally maps cores onto an NoC architecture such that either the energy consumption or the congestion is minimized. We propose a many-to-many core-switch mapping (mCSM) that allows a switch (core) to have multiple connections to its adjacent cores (switches). We also present decomposition methods that can obtain the suboptimal solutions with enhanced computational efficiency. Our work is the first to provide an exact mixe

The emerging High Efficiency Video Coding (HEVC) standard attempts to improve the coding efficiency by a factor of two over H.264/AVC using new compression tools with high computational complexity. The increased computational complexity makes the real-time execution with reasonable computing power become one of the critical concerns for the commercialization of HEVC. A large number of prediction modes are the main causes of the increased complexity of HEVC. Thus, a fast decision of a prediction

Weakly-supervised instance segmentation (WSIS) has been considered as a more challenging task than weakly-supervised semantic segmentation (WSSS). Compared to WSSS, WSIS requires instance-wise localization, which is difficult to extract from image-level labels. To tackle the problem, most WSIS approaches use off-the-shelf proposal techniques that require pre-training with instance or object level labels, deviating the fundamental definition of the fully-image-level supervised setting. In this pa

This paper presents a novel processing time control algorithm for a hardware-based H.264/AVC encoder. The encoder employs three complexity scaling methods partial cost evaluation for fractional motion estimation (FME), block size adjustment for FME, and search range adjustment for integer motion estimation (IME). With these methods, 12 complexity levels are defined to support tradeoffs between the processing time and compression efficiency. A speed control algorithm is proposed to select the com

A high-profile H.264 intra-frame encoder is suitable for low-cost and low-power applications and capable of providing enhanced compression efficiency. The high-profile is targeting the high-resolution videos. Thus, the encoding speed should be faster than or comparable to the baseline-profile. In previous work related to a hardware-based baseline-profile intra-frame encoder, a speed-up is achieved by the early termination of the intra modes and by an increase in the rate of hardware utilization

Early direct mode decision is a popular technique to improve the execution speed of inter-predictions in a B slice. However, the improvement is limited when this technique is applied to a hardware-based pipelined architecture or to the video sequences where the ratio of macroblocks (MBs) encoded as the direct mode is low. This paper proposes a novel fast inter-prediction algorithm for B slices which increases the encoding speed by early decision of the direction of the inter-prediction using spa

High-Efficiency Video Coding (HEVC) is the latest video coding standard, in which the compression performance is double that of its predecessor, the H.264/AVC standard, while the video quality remains unchanged. In HEVC, the test zone (TZ) search algorithm is widely used for integer motion estimation because it effectively searches the good-quality motion vector with a relatively small amount of computation. However, the complex computation structure of the TZ search algorithm makes it difficult

Noise, which is commonly generated in low-light environments or by low-performance cameras, is a major cause of the degradation of compression efficiency. In previous studies that attempted to combine a denoise algorithm and a video encoder, denoising was used independently of the code for pre-processing or post-processing. However, this process must be tightly coupled with encoding because noise affects the compression efficiency greatly. In addition, this represents a major opportunity to redu

Since the advent of computers, computing performance has been steadily increasing. Moreover, recent technologies are mostly based on massive data, and the development of artificial intelligence is accelerating it. Accordingly, various studies are being conducted to increase the performance and computing and data access, together reducing energy consumption. In-memory computing (IMC) and in-storage computing (ISC) are currently the most actively studied architectures to deal with the challenges o

The emerging High Efficiency Video Coding (HEVC) standard attempts to improve the coding efficiency by a factor of two over H.264/AVC through the use of new compression tools with high computational complexity. Although multipledirectional prediction is one of the features contributing to the improved compression efficiency, the computational complexity for prediction increases significantly. This paper presents an early uni-directional prediction decision algorithm. The proposed algorithm takes

The multiple-reference-frame motion estimation (ME) is one of the features to improve the compression efficiency. However, the computational complexity for prediction increases in proportion to the number of reference frames. This paper proposes the reference frame selection algorithm for a hardware-based HEVC encoder. The integer-ME explores multiple reference frames to find the best one and the fractional ME is then performed for the best reference frame which is determined by the IME. Simulat

Abstract Conventional bitrate control algorithms that change only the quantization parameter (QP) often suffer from quality degradation when the target bitrate is very low. Therefore, rate control algorithms that adjust spatial resolution in addition to QP control have recently been proposed, but their computations are too complex to be processed in real time. This research proposes a very simple, but effective, rate control algorithm that employs spatial resolution control as well as the existi

The emerging high-efficiency video coding (HEVC) standard attempts to improve the coding efficiency by a factor of two over H.264/AVC through the use of new compression tools such as various block sizes with multiple directions. Although multiple-directional predictions are among the features contributing to the improved compression efficiency, its high computational complexity keeps it from being used widely. This paper presents an algorithm to skip backward and bi-directional predictions when

Multi-view or light field images have recently gained much attraction from academic and commercial fields to create breakthroughs that go beyond simple video-watching experiences. Immersive virtual reality is an important example. High image quality is essential in systems with a near-eye display device. The compression efficiency is also critical because a large amount of multi-view data needs to be stored and transferred. However, noise can be easily generated during image capturing, and these