Dynamic Voltage and Frequency Scaling (DVFS) is an effective low-power technique for real-time workloads. Its effectiveness critically depends on the accurate prediction of the task execution time. Many DVFS approaches have been proposed, but they are insufficient for highly nonstationary workloads. Several recent DVFS techniques adopted adaptive filters to improve accuracy. However, their improvement was rather limited, since they mainly focused on applying a filter framework to the target application without tuning it. We address this issue by proposing Particle Filter (PF)-based video decoders (MPEG2 and H.264) which exploit application-specific characteristics. More specifically, our PF-based video decoders utilize the size of each frame for the prediction of its decoding time. Compared to previous work, the PF is more suitable for our purpose, since it achieves higher prediction accuracy, even for highly nonstationary workloads such as H.264 clips. Our results show that the energy saved by the proposed approach is comparable to that of the ideal policy called oracle-DVFS, while the existing methods we tested were far inferior to oracle-DVFS in terms of H.264 video decoding. Additionally, when our method was used, only 0.40 and 6.88 percent of the frames missed their deadlines with negligible computational overhead for MPEG and H.264, respectively.

Although the current standards (MPEG1, MPEG2, MPEG4, H.261, H.263, and H.264/MPEG4 AVC) as well as the recent VC-1, present the same basic functional elements, i.e., prediction, transformation, quantization, and entropy encoding, important changes occur in the details of each functional element. One of the details concerns the elimination of the loss in interblock correlation due to block-based prediction, transformation, and quantization. In order to overcome the loss in blocking artifacts, a deblocking filtering method is necessary to maximize coding performance and consequently improve image quality. This letter describes a programmable VC-1 deblocking filter architecture with capabilities to support different standards. The architecture has been modeled, simulated, and implemented at the register transfer level. Results show a threefold performance improvement as compared to solutions where filtering algorithms are otherwise not hardwired. Results also point to parallelism based on existing data flow, and show that real-time requirements can be met.

VC-1 is now one of the three video coding standards for high definition DVD that include MPEG-2 and H.264. The coded is expected to be used in consumer electronic devices such as DVD and camcorders. The H.264 format has begun to see strong acceptance and is used in mobile devices such as iPod and mobile phones. While multi-format DVD players are expected to support the three high definition video coding formats, H.264 is expected to have broader support in devices and video download services. The need to move data among devices with different capabilities creates a need for transcoding. In this paper we present a P-frame transcoder for VC-1 to H.264 transcoding. The transcoder exploits the variable size transform used in VC-1 to select the variable block size for motion compensation in H.264. The transcoder reduces the complexity substantially without significant loss in quality.

The high definition video adoption has been growing rapidly for the last two years. The two high definition DVD formats HD-DVD and Blueray have mandated MPEG-2, H.264 and VC-1 as video compression formats. The coexistence of these different video coding standards creates a need for transcoding. In this paper, an efficient transcoding algorithm from VC-1 video to H.264 video is discussed. While there has been recent work on MPEG-2 to H.264 transcoding, the published work on VC-1 to H.264 transcoding is non-existent. There is very limited amount of published work on VC-1. This paper gives a brief overview of VC-1 and discusses the opportunities for low-complexity tools for VC-1 to H.264 transcoding. The paper considers I and P frame transcoding from VC-1 to H.264 and proposes two approaches 1) low cost design and 2) high cost design

We propose the concept of spatio-temporal model-assisted compatible coding, a technique that selectively encodes areas of different importance to the human eye in terms of space and time in moving images. Our motivation is the fact that eye contact and lip synchronization are very important in person-to-person communication. Several areas including the eyes and lips require different types of quality since they have different perceptual significance to human observers. For example, for the eyes, high resolution is needed for clear communication, while for the lips frequent refresh is desirable. Fully automatic algorithms are described for performing model area detection and motion tracking. An area-selective (AS) rate control scheme is proposed, in order to effect AS bit allocation. It extends prior work that dealt with only the spatial dimensions to include the temporal aspects of the video signal as well. The decoder does not need to be changed in any way although the encoder's rate control unit is modified. As a result, the scheme can be used in compliance with standards-based codecs. As the scene model is only used in the rate control module (hence the term "model-assisted"), the technique does not suffer from the artifacts associated with model-based coding. Extensive experimental results are provided using ITU-T H.263, addressing very low bit-rate compression (below 64 kb/s).

We propose an optimal buffered compression algorithm for shape coding as defined in the forthcoming MPEG-4 international standard. The MPEG-4 shape coding scheme consists of two steps: first, distortion is introduced by down and up scaling; then, context-based arithmetic encoding is applied. Since arithmetic coding is "lossless," the down up scaling step is considered as a virtual quantizer. We first formulate the buffer-constrained adaptive quantization problem for shape coding, and then propose an algorithm for the optimal solution under buffer constraints. Previously, the fact that a conversion ratio (CR) of 1/4 makes a coded image irritating to human observers for QCIF size was reported for MPEG-4 shape coding. Therefore, careful consideration for small size images such as QCIF should be given to prevent coded images from being unacceptable. To this end, a low bit rate tuned algorithm is proposed in this paper as well. Experimental results are given using an MPEG-4 shape codec.

The extensive use of discrete transforms in image and video coding suggests the investigation on filtering before downsampling (FBDS) and filtering after upsampling (FAUS) methods directly acting on the transform domain. We describe the "transform-damain resolution translation" technique that gives flexibility to resize windows of each video conferencing session for a server compositing without explicit decompression, spatial domain processing, and compression. We generalize transform-domain filtering (TDF) to include nonuniform and multirate cases to implement the transform-domain resolution translator. The former is defined as a TDF problem in which the original transform-domain is of different size from the target one, while the latter considers the implementation of sampling rate conversion in the transform-domain. The implementation architecture is based on a pipeline that involves matrix-vector product blocks and vector addition, but is not limited to particular hardware. Such techniques are particularly useful for fast algorithms for processing compressed images and video where transform coding is extensively used (e.g., in JPEG, H.261, MPEG-1, MPEG-2, and H.363).

The current MPEG-4 shape coding scheme is "bitmap-based", and consists of two steps: first, distortion is introduced by down and up scaling; then, context-based arithmetic encoding is applied. Recently bitmap-based methods have been reported to produce more irritating images than contour-based methods, while introducing a similar amount of quantization error. In this paper, we propose four morphological enhancement methods which can be used in the current MPEG-4 shape decoding process. In addition, we devise a way to let decoders know which method is the best of those four morphological operations, thus preventing post-processing processes from being "blind" about the original source images. Experimental results are given using an MPEG-4 shape codec with morphological operations.

In this paper, we derive an optimal rate control algorithm for shape coding as defined in the forthcoming MPEG-4 international standard. The current MPEG-4 shape coding scheme consists of two steps: first, distortion is introduced by down and up scaling; then, context-based arithmetic encoding is applied. Since arithmetic coding is "lossless", the down up scaling step is considered as a virtual quantizer. We first formulate the buffer-constrained adaptive quantization problem for shape coding, and then propose an algorithm for the optimal solution under buffer constraints. Experimental results are given using an MPEG-4 shape codec.

We introduce the concept of spatio-temporal model-assisted compatible (STMAC) coding, a technique to selectively encode areas of different importance to the human eye in terms of space and time in moving images. For this, we use the fact that human "eye contact" and "lip synchronization" are very important in person-to-person communication. Several areas including the eyes and lips need different types of quality, since different areas have different perceptual significance to human observers. For example, for the eyes "high resolution" is needed for clear communication, while for the lips "frequent refresh" is needed. The approach provides a better rate-distortion tradeoff than conventional image coding technologies based on MPEG-1, MPEG-2, H.261, as well as H.263, since STMAC coding is applied on top of an encoder, taking full advantage of its core design. The decoder does not need to be changed in any way although the encoder's rate control unit is slightly modified. This characteristic leads to the name "compatible" in the proposed concept. Experimental results are given using ITU-T H.263, addressing very low bit rate compression (13-17 Kbps).