We propose a novel motion estimation compensation (ME MC) method for wavelet-based (in-band) motion compensated temporal filtering (MCTF), with application to low-bitrate video coding. Unlike the conventional in-band MCTF algorithms, which require redundancy to overcome the shift-variance problem of critically sampled (complete) discrete wavelet transforms (DWT), we perform ME MC steps directly on DWT coefficients by avoiding the need of shift-invariance. We omit upsampling, the inverse-DWT (IDWT), and the calculation of redundant DWT coefficients, while achieving arbitrary subpixel accuracy without interpolation, and high video quality even at very low-bitrates, by deriving the exact relationships between DWT subbands of input image sequences. Experimental results demonstrate the accuracy of the proposed method, confirming that our model for ME MC effectively improves video coding quality.
All MCTF methods summarized above perform motion estimation motion compensation either in the temporal domain before DWT, or in the wavelet domain with the help of redundancy (e.g. ODWT, DT-CW, etc.), due to the fact that complete DWT is shift-variant and motion estimation directly on DWT subbands is a challenging task. However, redundancy in these methods leads to high computational complexity @cite_8 . Inspired by the fact that shift variance keeps the perfect reconstruction and nonredundancy properties of wavelets and breaks the coupling between spatial subbands, and that wavelet codecs always operate on complete DWT subbands @cite_6 , we propose a novel in-band ME MC method, which avoids the need of shift invariance, and operates directly on the original DWT coefficients of the input sequences. Since Haar wavelets are widely utilized in MCTF methods due to the coding efficiency based on their short kernel filters @cite_6 , our method is built on Haar subbands. For accurate ME MC, we define the exact relationships between the DWT subbands of input video sequences, which allows us to avoid upsampling, inverse DWT, redundancy, and interpolation for subpixel accuracy.
@cite_6 @cite_8
1987262412 2100564571 2138313367 2110772958
Motion estimation and compensation in wavelet domain have received much attention recently. To overcome the inefficiency of motion estimation in critically sampled wavelet domain, the low-band-shift (LBS) method and the complete-to-overcomplete discrete wavelet transform (CODWT) method are proposed for motion estimation in shift-invariant wavelet domain. However, a major disadvantage of these methods is the computational complexity. Although the CODWT method has reduced the computational complexity by skipping the inverse wavelet transform and making the direct link between the critically sampled subbands and the shift-invariant subbands, the full search algorithm (FSA) increases it. In this paper, we proposed two fast multiresolution motion estimation algorithms in shift-invariant wavelet domain: one is the wavelet matching error characteristic based partial distortion search (WMEC-PDS) algorithm, which improves computational efficiency of conventional partial distortion search algorithms while keeping the same estimate accuracy as the FSA; another is the anisotropic double cross search (ADCS) algorithm using multiresolution-spatio-temporal context, which provides a significantly computational load reduction while only introducing negligible distortion compared with the FSA. Due to the multiresolution nature, both the proposed approaches can be applied to wavelet-based scalable video coding. Experimental results show the superiority of the proposed fast motion estimation algorithms against other fast algorithms in terms of speed-up and quality. The discrete wavelet transform (DWT) has several advantages of multiresolution analysis and subband decomposition, which has been successfully used in image processing. However, the shift-variant property is intrinsic due to the decimation process of the wavelet transform, and it makes the wavelet-domain motion estimation and compensation inefficient. To overcome the shift-variant property, a low-band-shift method is proposed and a motion estimation and compensation method in the wavelet-domain is presented. The proposed method has a superior performance to the conventional motion estimation methods in terms of the mean absolute difference (MAD) as well as the subjective quality. The proposed method can be a model method for the motion estimation in wavelet-domain just like the full-search block matching in the spatial domain. We consider the problems of motion-compensated frame interpolation (MCFI) and bidirectional prediction in a video coding environment. These applications generally require good motion estimates at the decoder. We use a multiscale optical-flow-based motion estimator that provides smooth, natural motion fields under bit-rate constraints. These motion estimates scale well with change in temporal resolution and provide considerable flexibility in the design and operation of coders and decoders. In the MCFI application, this estimator provides excellent interpolated frames that are superior to those of conventional motion estimators, both visually and in terms of peak signal-to-noise ratio (PSNR). We also consider the effect of occlusions in the bidirectional prediction application and introduce a dense label field that complements our motion estimator. This label field enables us to adaptively weight the forward and backward predictions and gives us substantial visual and PSNR improvements in the covered uncovered regions of the sequence. A new transform is proposed that derives the overcomplete discrete wavelet transform (ODWT) subbands from the critically sampled DWT subbands (complete representation). This complete-to-overcomplete DWT (CODWT) has certain advantages in comparison to the conventional approach that performs the inverse DWT to reconstruct the input signal, followed by the a spl grave -trous or the lowband shift algorithm. Specifically, the computation of the input signal is not required. As a result, the minimum number of downsampling operations is performed and the use of upsampling is avoided. The proposed CODWT computes the ODWT subbands by using a set of prediction-filter matrices and filtering-and-downsampling operators applied to the DWT. This formulation demonstrates a clear separation between the single-rate and multirate components of the transform. This can be especially significant when the CODWT is used in resource-constrained environments, such as resolution-scalable image and video codecs. To illustrate the applicability of the proposed transform in these emerging applications, a new scheme for the transform-calculation is proposed, and existing coding techniques that benefit from its usage are surveyed. The analysis of the proposed CODWT in terms of arithmetic complexity and delay reveals significant gains as compared with the conventional approach.