By Huifang Sun
Pros within the video and multimedia industries want a e-book that explains criteria for video coding and the way to transform the compressed details among criteria. electronic Video Transcoding for Transmission and garage solutions this call for whereas additionally providing the theories and rules of video compression and transcoding applied sciences. Emphasizing electronic video transcoding recommendations, this ebook summarizes its content material through examples of functional equipment for transcoder implementation. It relates just about all of its featured transcoding applied sciences to functional applications.
This quantity takes a established technique, beginning with uncomplicated video transcoding techniques and progressing towards the main refined platforms. It summarizes fabric from learn papers, lectures, and shows. prepared into 4 components, the textual content first offers the history of video coding conception, ideas of video transmission, and video coding criteria. the second one half comprises 3 chapters that specify the speculation of video transcoding and sensible difficulties. The 3rd half explores buffer administration, packet scheduling, and encryption within the transcoding. The publication concludes via describing the applying of transcoding, common multimedia entry with the rising MPEG-21 typical, and the end-to-end try out mattress
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Additional resources for Digital Video Transcoding for Transmission and Storage
In particular, we will study the Karhunen-Loève transform, discrete cosine transform, integer discrete cosine transform, subband decomposition and discrete wavelet transform. 9 Histogram of DCT coefﬁcients. 1 KARHUNEN-LOÈVE TRANSFORM To fully exploit spatial redundancy, it is known that the Karhunen-Loève transform can provide the optimal solution. The rows of the discrete Karhunen-Loève transform consist of the eigenvectors for the autocorrelations matrix. The autocorrelation matrix for a stationary discrete random process X(N) is given by ⎡ E( X12 ) ⎢ R=⎢ ⎢ ⎢ ⎢⎣ E( Xn X1 ) ⎡ RX (0) ⎢ =⎢ ⎢ ⎢ ⎣ RX ( N − 1) E( X1 X2 ) E( X22 ) E( Xn X2 ) RX (1) RX (0) RX ( N − 2) E( X1 Xn )⎤ ⎥ ⎥ ⎥ 2 ⎥ E( Xn ) ⎥⎦ L O L L O L RX ( N − 1)⎤ ⎥ ⎥ ⎥ ⎥ RX (0) ⎦ It can be shown that this transform will minimize the geometric mean of the variance of the transform coefﬁcients.
This algorithm offers six times faster speed compared to the conventional approach using double-size FFT [1-18]. 4 INTEGER DISCRETE COSINE TRANSFORM In the MPEG-1/2/4 standards, the residual signal after motion compensation is compressed with 8 × 8 ﬂoating-point precision DCT transform. For practical applications the ﬂoating-point transform is implemented with a ﬁnite precision. There is a mismatch Fundamentals of Digital Video Compression 19 in the computation of DCT and IDCT at both the encoder and decoder.
Based on a single wavelet prototype function ψ (t) with only shifting and scaling, one can construct a family of orthonormal bases ψmn (t) as follows. , such a ﬁlter converges to a continuous and differentiable function φ (t). Daubechies shows that the sufﬁcient conditions for regularity can be obtained by placing a maximum number of zeros at w = π and maintaining the orthogonality condition. Daubechies also provides a construction method to achieve regularity [1-30]. 15 with three levels of wavelet analysis.