Efficient Hybrid DCT-Domain Algorithm for Video Spatial Downscaling

Abstract

A highly efficient video downscaling algorithm for any arbitrary integer scaling factor performed in a hybrid pixel transform domain is proposed. This algorithm receives the encoded DCT coefficient blocks of the input video sequence and efficiently computes the DCT coefficients of the scaled video stream. The involved steps are properly tailored so that all operations are performed using the encoding standard block structure, independently of the adopted scaling factor. As a result, the proposed algorithm offers a significant optimization of the computational cost without compromising the output video quality, by taking into account the scaling mechanism and by restricting the involved operations in order to avoid useless computations. In order to meet any system needs, an optional and possible combination of the presented algorithm with high-order AC frequency DCT coefficients discarding techniques is also proposed, providing a flexible and often required complexity scalability feature and giving rise to an adaptable tradeoff between the involved scalable computational cost and the resulting video quality and bit rate. Experimental results have shown that the proposed algorithm provides significant advantages over the usual DCT decimation approaches, both in terms of the involved computational cost, the output video quality, and the resulting bit rate. Such advantages are even more significant for scaling factors other than integer powers of 2 and may lead to quite high PSNR gains.

Minimum adder-delay architecture of 8/16/32-point DCT based on fixed-rotation adaptive CORDIC

“…DCT was an irreplaceable step of many compression algorithms such as JPEG [2], MPEG1 [3], H.264 [4], and the latest video coding of High-Efficiency Video Coding (HEVC) [5]. On the development trend of video coding recently, the requirements for such a DCT implementation are increasing rapidly, especially in timing performances.…”

A class of DCT approximations based on the Feig–Winograd algorithm

“…Noteworthy DCT methods include the following procedures: Wang factorization [27], Lee DCT for power-of-two block lengths [28], Arai DCT scheme [29], Loeffler algorithm [30], and Feig-Winograd factorization [31]. All these algorithms are classical results in the field and have been considered for practical applications [9,32,33]. For instance, the Arai DCT scheme was employed in various recent hardware implementations of the DCT [34][35][36].…”

“…instance, although the new matrix T(9) 8 is not explicitly listed in literature, it is equivalent to the Lengwehasatit-Ortega approximation T(1) …”

Area and power efficient DCT architecture for image compression

“…Due to this fact, discrete cosine transform is the finest substitute for the KLT. Indeed, DCT has found applications in many image and video compression standard such as JPEG [4], MPEG-1 [5], MPEG-2 [6], H.261 [7], H.263 [8], and H.264/AVC [9,10]. During the JPEG process, an image is divided into several 8 × 8 blocks and then the two-dimensional discrete cosine transform In general, the floating point DCT decorrelates the data being transformed so that most of its energy is packed in the low-frequency region, which is best suited for well-known image compression techniques [11][12][13][14][15] but does not meet the requirements of very fast real-time compression applications.…”