Integer DCT Research Articles

Compressed domain content based retrieval using H.264 DC-pictures

A fast and simple method for content based retrieval using the DC-pictures of H.264 coded video without full decompression is presented. Compressed domain retrieval is very desirable for content analysis and retrieval of compressed image and video. Even though, DC-pictures are among the most widely used compressed domain indexing and retrieval methods in pre H.264 coded videos, they are not generally used in the H.264 coded video. This is due to two main facts, first, the I-frame in the H.264 standard are spatially predicatively coded and second, the H.264 standard employs Integer Discrete Cosine Transform. In this paper we have applied color histogram indexing method on the DC-pictures derived from H.264 coded I-frames. Since the method is based on independent I-frame coded pictures, it can be used either for video analysis of H.264 coded videos, or image retrieval of the I-frame based coded images such as advanced image coding. The retrieval performance of the proposed algorithm is compared with that the fully decoded images. Simulation results indicate that the performance of the proposed method is very close to the fully decompressed image systems. Moreover the proposed method has much lower computational load.

Digital image authentication and recovery: Employing integer transform based information embedding and extraction

Recently, several semi-fragile watermarking approaches with the additional capability of image recovery have been proposed. However, the security, robustness, and image recovery aspect of these approaches have certain shortcomings. In this paper, a novel semi-fragile watermarking framework using integer transform based information embedding and extraction is proposed, which allows accurate authentication and recovery of the image. It is based on integer wavelet transform with improved security against collage attack, enhanced robustness, and capability of producing better quality recovered image. Security is enhanced by correlating the to-be-embedded watermark with the approximation subband of wavelet transform. Similarly, no unprotected area is left for attacks on the image, either in spatial or transform domain. Robustness is enhanced by using the idea of embedding in largest coefficient inside a group and correlating it with the quantized version of the mean of the group. In particular, the recovery approach is improved by introducing lossless compression and BCH coding of the integer DCT based low-pass version of the cover image itself. Alteration sensitivity is improved compared to traditional block-based approaches and thus the proposed approach can concisely determine the regions where the integrity verification fails. Experimental comparisons with existing approaches validate the usefulness of the proposed multiple semi-fragile watermarking approach.

An efficient macroblock-based diverse and flexible prediction modes selection for hyperspectral images coding

In this paper, an efficient macroblock-based diverse and flexible prediction modes selection algorithm is proposed for coding hyperspectral images, which is inspired by the prediction scheme of H264/AVC. Here, different modes are specified for the corresponding macroblocks (16×16 pixel regions of a band) of hyperspectral images other than the whole band image using only one reference band image for prediction. Only the 4×4 mode is employed for the intra-band prediction in view of the fact that correlation coefficients of pixels separated by not more than four pixels in the spatial domain are greater than 0.65 at most cases. The optimal reference band is determined by the fast reference band selection algorithm; thereafter, the best partition of the candidate macroblock in the optimal reference band is further selected for inter-band prediction of the current macroblock. Thus, the stronger correlation in the spectral direction or in the spatial domain is utilized for the prediction of the given macroblock. With a comparably low memory requirement, the prediction coding scheme is proposed to speed up the implemental process using the fast reference band selection algorithm, the integer DCT and the quantization, which just needs the multiplication and bit-shifts operations. Several AVIRIS images are used to evaluate the performance of the algorithm. The proposed scheme outperforms the state-of-the-art 3D-based compression algorithms at lower rates. Moreover, compared with the method by using all the prediction modes of H.264/AVC, about 80% encoding time can be saved by our method under the same experimental condition.

Fast and low complexity method for content accessing and extracting DC-pictures from H.264 coded videos

A fast and simple method for content accessing and extracting the DC-pictures of H.264 coded video without full decompression is presented. Since DC-pictures are used in various applications such as compressed domain analysis or indexing of visual data, several methods for extracting DC-pictures of non-integer DCT codecs have been proposed. However, these methods are not efficient for the H.264 codec that uses integer DCT transform, which employs only shift and add operations and already has lower computational load than the non-integer DCT transform. In this paper we propose a fast and low complexity method to extract DC-pictures of H.264 coded videos with significant lower computational cost compared to its full decompression.

Integer DCT Based on Direct-Lifting of DCT-IDCT for Lossless-to-Lossy Image Coding

A discrete cosine transform (DCT) can be easily implemented in software and hardware for the JPEG and MPEG formats. However, even though some integer DCTs (IntDCTs) for lossless-to-lossy image coding have been proposed, such transform requires redesigned devices. This paper proposes a hardware-friendly IntDCT that can be applied to both lossless and lossy coding. Our IntDCT is implemented by direct-lifting of DCT and inverse DCT (IDCT). Consequently, any existing DCT device can be directly applied to every lifting block. Although our method requires a small side information block (SIB), it is validated by its application to lossless-to-lossy image coding.

H.264/AVC에서 3차원 변환에 기반을 둔 효율적인 동영상 압축 방법

본 논문에서는 H.264/AVC에서 사용하는 정수형 변환을 <TEX>$4{\times}4$</TEX> 블록 단위로 적용하고 인접 네 개의 <TEX>$4{\times}4$</TEX> 블록의 같은 주파수 위치의 계수값을 모아서 추가로 <TEX>$4{\times}1$</TEX> 블록 단위로 1차원 변환하는 3차원 변환(3DT : Dimensional Transform)을 기반으로 부호화 방법을 통합한 환경인 3DTE(3DT Environment)를 제안한다. 제안하는 방법에서 사용하는 변환인 3DT는 H.264/AVC가 가지는 예측오차를 유지하면서 인접블록 간에 남아있을 공간적 중복도를 추가로 줄일 수 있고 이와 같은 특성에 적합한 방법을 적용하였다. 본 논문의 실험에서 제안하는 방법은 JM11.0과 비교 실험했을 때 대표적인 시험 시퀀스에 대하여 High profile 환경에서 평균적으로 약 3.58% 정도의 비트율 절감을 얻었다. 특히 HD급과 같이 해상도가 높은 영상에서 평균 약 5.40% 정도의 높은 비트율 절감을 보였다. In this paper, we propose 3DTE(3-Dimensional Transform Environment) that is based on 3DT(Dimensional Transform) that performs 2-dimensional integer DCT(Discrete Cosine Transform) based on <TEX>$4{\times}4$</TEX> block and 1-dimensional integer DCT based on <TEX>$4{\times}1$</TEX> block after collecting same frequency coefficients in neighboring <TEX>$4{\times}4$</TEX> block and supports it's additional coding tools for high performance. The transform of 3DT can keep prediction error by using <TEX>$4{\times}4$</TEX> block and reduce spatial redundancy additionally. The proposed 3DTE can provide coding tools to improve the coding efficiency with using 3DT. The performance of 3DTE compared to JM11.0 is average 3.58% and 5.40% bit savings for all test sequences and HD sequences, respectively, with keeping subjective video quality in High profile.

Integer Discrete Cosine Transform via Lossless Walsh-Hadamard Transform with Structural Regularity for Low-Bit-Word-Length

This paper presents an integer discrete cosine transform (IntDCT) with only dyadic values such as k/2n (k, $n\in\mathbb{N}$). Although some conventional IntDCTs have been proposed, they are not suitable for lossless-to-lossy image coding in low-bit-word-length (coefficients) due to the degradation of the frequency decomposition performance in the system. First, the proposed M-channel lossless Walsh-Hadamard transform (LWHT) can be constructed by only (log2M)-bit-word-length and has structural regularity. Then, our 8-channel IntDCT via LWHT keeps good coding performance even if low-bit-word-length is used because LWHT, which is main part of IntDCT, can be implemented by only 3-bit-word-length. Finally, the validity of our method is proved by showing the results of lossless-to-lossy image coding in low-bit-word-length.

Image Resizing on the Integer DCT Domain Used in H.264/AVC

In this paper, we propose a method of resizing images in the integer DCT domain employed by H.264/AVC. To accomplish this, we first derive the matrix scaling the image resolution, and then factorize the scaled DCT blocks and the post scaling factors (PF) from the matrix obtained from the multiplication of the scaling matrix and the original integer DCT blocks. Then, we separate the scaled DCT blocks into the integer scaling matrix and the scaled integer DCT blocks. The experiments show that the proposed method produces nearly the same performance as those operating in the real DCT domain.

Hybrid Model to Detect Zero Quantized DCT Coefficients in H.264

In H.264 coding, there are a large number of discrete cosine transform (DCT) coefficients of the prediction residue which are quantized to zeros. Therefore, it is desired to design a method which can early detect zero quantized DCT coefficients (ZQDCT) before implementing DCT and quantization (Q) and thus reduce redundant computations for H.264 coding. To achieve this, a hybrid model is proposed in this paper in order to predict ZQDCT coefficients. First, the Gaussian distribution is applied to study the integer DCT coefficients in H.264 and hence an adaptive scheme with multiple thresholds is derived to realize different types of DCT and Q implementations. Then the adaptive scheme is further optimized by considering a more efficient condition to sufficiently detect all-zero DCT blocks. As a result, a hybrid model is developed. Compared with other methods in the literature, the proposed hybrid model is able to detect more ZQDCT coefficients and hence reduce more computations for H.264 encoding. It is shown by experimental results that the proposed hybrid model can achieve the best performance in reducing computations and obtain almost the same rate-distortion (R-D) performance as the original encoder in the H.264 reference software JM9.5

Efficient prediction algorithm of integer DCT coefficients for H.264/AVC optimization

This paper presents a novel efficient prediction algorithm to reduce redundant discrete cosine transform (DCT) and quantization computations for H.264 encoding optimization. A theoretical analysis is performed to study the sufficient condition for DCT coefficients to be quantized to zeros. As a result, three sufficient conditions corresponding to three types of transform and quantization methods in H.264 are proposed. Compared with other algorithms in the literature, the proposed algorithm derives more precise and efficient conditions to predict zero quantized DCT coefficients. Both the theoretical analysis and experimental results demonstrate that the proposed algorithm is superior to other algorithms in terms of the computational complexity reduction, encoded video quality, false acceptance rate, and false rejection rate.

Worst-case error analysis of lifting-based fast DCT-algorithms

Integer DCTs have a wide range of applications in lossless coding, especially in image compression. An integer-to-integer DCT of radix-2-length n is a nonlinear, left-invertible mapping, which acts on /spl Zopf//sup n/ and approximates the classical discrete cosine transform (DCT) of length n. All known integer-to-integer DCT-algorithms of length 8 are based on factorizations of the cosine matrix C/sub 8//sup II/ into a product of sparse matrices and work with lifting steps and rounding off. For fast implementation one replaces floating point numbers by appropriate dyadic rationals. Both rounding and approximation leads to truncation errors. In this paper, we consider an integer-to-integer transform for (2/spl times/2) rotation matrices and give estimates of the truncation errors for arbitrary approximating dyadic rationals. Further, using two known integer-to-integer DCT-algorithms, we show examplarily how to estimate the worst-case truncation error of lifting based integer-to-integer algorithms in fixed-point arithmetic, whose factorizations are based on (2/spl times/2) rotation matrices.

A New Unified Lossless/Lossy Image Compression Based on a New Integer DCT

In this paper, we propose a new one-dimensional (1D) integer discrete cosine transform (Int-DCT) for unified lossless/lossy image compression. The proposed 1D Int-DCT is newly designed to reduce rounding effects by minimizing number of rounding operations. The proposed Int-DCT can be operated not only lossless coding for a high quality decoded image but also lossy coding for a compatibility with the conventional DCT-based coding system. Both theoretical analysis and simulation results confirm an effectiveness of the proposed Int-DCT.

Efficient discrete cosine transform and quantization algorithm based on eliminating redundant computations in H.264 video encoding

We propose a new efficient discrete cosine transform (DCT) and quantization algorithm for the H.264 encoder. We theoretically analyze integer DCT and quantization of the H.264 encoder. A theoretical analysis shows that there are redundant calculations for DCT and quantization. In the proposed algorithm, one of four methods—1. DCT skip; 2. reduced DCT1; 3. reduced DCT2; 4. original DCT—is selected by using the minimum SAD information obtained in the motion estimation. The reduced DCT1 and reduced DCT2 eliminate the redundant calculations required for DCT and quantization. The simulation results show that the proposed algorithm achieves an approximately 15 to 25% computational saving without video-quality degradation, compared to the conventional method.

Early detection method of all-zero integer transform coefficients

The new H.264 video coding standard has a significant performance benefit versus older standards in compression performance. Unfortunately, it also has a considerable increase in encoder complexity. In this paper, we extend and adapt the concept of detection of all-zero quantization coefficients before transformation and quantization. A guideline for miss detection and false detection is proposed according to the principle of two-dimensional integer DCT and quantization in H.264. With this guideline, a generalized discriminant that can be applied to different integer transforms is also provided. It is the so-called early detection method of all-zero integer DCT coefficients (EDMAIDC). Simulation results demonstrate the efficiency of proposed algorithm of reducing encoding complexity while incurring no loss in quality.

Optimum word length allocation of integer DCT and its error analysis

Recently, the integer DCT (Int-DCT), which transforms an integer input to an integer output, is attracting many researchers’ attention as an effective method for DCT-based lossy/lossless unified coding. So far, there are many reports relevant to the Int-DCT, but they have been limited to a few topics such as how to reduce the number of multipliers with the four-point lossless Hadamard transform and the non-separable two-dimensional Int-DCT. However, none of them is focused on how to express the multipliers’ word length as short as possible for the reduction of hardware complexity. In this report, we define a new “SNR sensitivity” as an indicator of how the word length truncation of multiplier coefficients affects quality of a reconstructed image. Based on the sensitivity, we propose a new word length allocation method. We also theoretically analyze errors in a reconstructed signal to confirm an effectiveness of the proposed method. As a result, the optimum word length allocation, which depends on a frequency spectrum of an input signal, significantly improves quality of a reconstructed image.

Fast loop filtering using separable characteristics of the integer 2-D discrete cosine transform

When an image is highly compressed, video coding using the discrete cosine transform (DCT) and quantization produces noticeable image degradations, such as blocking artifacts and ringing noise. In order to reduce the degradations, a loop filtering algorithm is proposed, which consists of simple deblocking filtering and a fast decision rule for ringing and blocking conditions. The proposed method utilizes a four-point integer DCT for detecting blocking and ringing conditions. It also adopts an early termination policy during detection of the blocking and ringing conditions in the DCT domain. This policy speeds up computation of the filtering. The proposed method is compared with the loop filtering of the Joint Video Team (JVT) codec. As an experimental result, the computation time of the proposed method is approximately 20% faster than that of the JVT loop filtering, while the PSNR is almost the same.

Invertible integer DCT algorithms

Integer DCTs have important applications in lossless coding. In this paper, an integer DCT of radix-2 length n is understood to be a nonlinear, (left-)invertible mapping which acts on Z n and approximates the classical discrete cosine transform (DCT) of length n. In image compression, the DCT of type II (DCT-II) is of special interest. In this paper we present a new approach to invertible integer DCT-II and integer DCT-IV. Our method is based on a factorization of the cosine matrices of types II and IV into products of sparse, orthogonal matrices. Up to some permutations, each matrix factor is a block-diagonal matrix with blocks being orthogonal matrices of order 2. Hence one has to construct only integer transforms of length 2. We factorize an orthogonal matrix of order 2 into three lifting matrices and work with lifting steps and rounding-off. This allows the construction of new integer DCT algorithms. We give uniform bounds for the worst case difference between the results of exact DCT and the corresponding integer DCT. Finally, we present some numerical experiments for the integer DCT-II of length 8 and for the 2-dimensional integer DCT-II of size 8×8.

Integer discrete cosine transform and its fast algorithm

A recursive sparse matrix decomposition for a floating-point discrete cosine transform (DCT) matrix is presented. Based on this matrix decomposition approach, a split-radix DCT algorithm is proposed and a new integer DCT (IntDCT) algorithm that requires only lifting steps and additions is developed.