L. G. Roberts, "Picture coding using pseudo random noise," IRE Transactions on Information Theory, vol. IT-8, pp. 145-154, Feb. 1962.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....statistical characterization of at the receiver. A similar type of control signal is often exploited in the context of lossy compression and is commonly referred to as nonsubtractive dithering; it has been shown to provide compression distortion improvements in the context of encoding of images [38] and audio [32] and more generally in the context of lossy compression (see [39] 40] 32] and the references therein) In general, wemay consider families of random control inputs parameterized by means of a scale parameter , where , and where is an admissible i.i.d. noise sequence with pdf ....

.... in particular, it is noteworthy that, besides the interesting connections between the feedback schemes to successive approximation A D converters, all the control input encoding techniques we have considered have similarities to nonsubtractive and subtractive dithering techniques [32] 33] [38], 43] 44] For instance, in both the known control input case and the feedback case, knowledge of the control input is exploited by the estimator and compensated after quantization, although, unlike subtractive dithering, the control input is not simply subtracted off the quantized signal, as ....

L. R. Roberts, "Picture coding using pseudo-random noise," IRE Trans. Inform. Theory, vol. IT-8, pp. 145--154, Feb. 1962.

.... more complex vector quantization algorithms like the LBG and ECVQ [1] 2] The geometric regularity of lattices allow very fast quantization algorithms, and there are already efficient algorithms for several well known lattice structures [3] 7] Dithering was first applied by Roberts [8] to image coding. It was seen that by adding an independent random variable called dither before the quantization and subtracting after it, the perceptual quality of the image improves substantially. After that pioneering idea, there has been considerable work on the theory and applications of ....

L.G. Roberts, "Picture coding using pseudo-random noise," IRE Trans. Information Theory, vol. IT-8, pp. 145-154, Feb. 1962.

....has also been recently mentioned in [270] One may note here that the process of thresholding with a dither array can be replaced by a mathematically equivalent scheme of adding a dither pattern to the image and thresholding at a constant level. This is a variant of the scheme proposed in [271]. The original scheme proposed the use of random noise as the dither pattern. Such a scheme is known to reduce visible artifacts due to quantization and is often used in monochrome and color displays. In order to emphasize the difference with this random dither, the term ordered dither is often ....

L. G. Roberts, "Picture coding using pseudo-random noise," IRE Trans. Inform. Theory, vol. IT-8, pp. 145--154, Feb. 1962.

....signal and the approximations are valid only under certain conditions. Signal independent quantization noise has generally been found to be perceptually desirable. This was the motivation for randomizing the action of quantization by the addition of a dither signal, a method introduced by Roberts [442] as a means of making quantized images look better by replacing the artifacts resulting from deterministic errors by random noise. We shall return to dithering in Section V, where it will be seen that suitable dithering can indeed make exact the Bennett GRAY AND NEUHOFF: QUANTIZATION 5 ....

....approach, dubbed gold washing did not involve training, but rather created and removed codevectors according to the data received and an auxiliary random process in a way that could be tracked by a decoder without side information. E. Dithering Dithered quantization was introduced by Roberts [442] in 1962 as a means of randomizing the e#ects of uniform quantization so as to minimize visual artifacts. It was further developed for images by Limb (1969) 317] and for speech by Jayant and Rabiner (1972) 266] Intuitively, the goal was to cause the reconstruction error to look more like ....

L. G. Roberts, "Picture coding using pseudo-random noise," IRE Trans. Inform. Theory, vol. 8, pp. 145--154, Feb. 1962.

....signal and the approximations are valid only under certain conditions. Signal independent quantization noise has generally been found to be perceptually desirable. This was the motivation for randomizing the action of quantization by the addition of a dither signal, a method introduced by Roberts [442] as a means of making quantized images look better by replacing the artifacts resulting from deterministic errors by random noise. We shall return to dithering in Section V, where it will be seen that suitable dithering can indeed make exact the Bennett GRAY AND NEUHOFF: QUANTIZATION 5 ....

....approach, dubbed gold washing did not involve training, but rather created and removed codevectors according to the data received and an auxiliary random process in a way that could be tracked by a decoder without side information. E. Dithering Dithered quantization was introduced by Roberts [442] in 1962 as a means of randomizing the effects of uniform quantization so as to minimize visual artifacts. It was further developed for images by Limb (1969) 317] and for speech by Jayant and Rabiner (1972) 266] Intuitively, the goal was to cause the reconstruction error to look more like ....

L. G. Roberts, "Picture coding using pseudo-random noise," IRE Trans. Inform. Theory, vol. 8, pp. 145--154, Feb. 1962.

....noise would in fact be a desirable attribute, as it would make quantized signals seem like a signal plus random noise instead of a signal marred by signal dependent artifacts. This was the motivation for randomizing the action by the addition of a dither signal, a method introduced by Roberts [310], as a means of making quantized images look better by replacing the artifacts resulting from deterministic errors by random noise. We shall return to dithering in Section 5, where it will be seen that dithering can indeed make the Bennett approximation exact. Bennett also used a variation on ....

....Recent combinations of TCQ to coding wavelet coefficients [324] have yielding excellent performance in image coding applications, winning the JPEG 2000 contest of 1997 and thereby a position as a serious contender for the new standard. Dithering Dithered quantization was introduced by Roberts [310] in 1962 as a means of randomizing the effects of uniform quantization so as to minimize visual artifacts. Intuitively, the goal was to cause the reconstruction error to look more like signal independent additive white noise. It turns out that for one type of dithering, this intuition is true. In ....

L. G. Roberts, "Picture coding using pseudo-random noise," IRE Trans. on Information Theory, Vol. 8, No. 2, pp. 145--154, Feb. 1962.

....is very fast when compared to other estimation techniques. Post processing techniques preserve the original bit rate obtained by the JPEG algorithms, since the JPEG output is unchanged. Many techniques in the literature reduce artifacts by altering the original algorithm. Robert s randomization [7] introduces uniform noise prior to quantization. Robert s approach improves the image quality by eliminating the banding artifact, but also tends to increase the bitrate [8] Other techniques define a cost function which may include a priori statistical information [9] 6] and then apply a ....

L. G. Roberts. Picture coding using pseudorandom noise. IRE Transactions, IT-8(2):145--154, 1962.

....better than the median cut method. The variance bisection method has not been implemented yet. THE ADDITION OF NOISE As mentioned before, the addition 49 noise to a severely quantized image can help remove quantization distortion. This was tried for monochromatic images by Goodall [16] and Roberts [42]. They found that black and white images can be quantized to 3 or 4 bits with good results. Huang et al. 20] point out that this noise addition succeeds because the eye objects more to structured noise than unstructured noise. The lesson is that it is best to transform quantization noise into ....

Roberts, L. G., "Picture Coding Using Pseudo-Random Noise," IRE Trans. on Information Theory, Vol. IT-8, Feb. 1962, p. 145.

....random signal or dither at the input of the quantizer. By suitably choosing the dither signal, one can in some cases force the quantization error to satisfy all aspects of the white noise approximation, but at the possible cost of corrupting the signal and reducing the allowed no overload range [21, 22, 23, 24]. The approach taken here is a variation of the classical characteristic function method of Rice [25] and the transform method of Davenport and Root [26] who represented memoryless nonlinearities using Fourier or Laplace transforms. A similar application of Fourier analysis was made to ....

L. G. Roberts, "Picture coding using pseudo-random noise," IRE Trans. on Information Theory, vol. IT8, pp. 145--154, February 1962.

....in [14] that this optimal lattice quantizer has the property that the vector Z K U(P 0 ) is white, i.e. EfZ K Z t K g = ffl Delta I ; 5) where I is the identity matrix. In general, QK is defined to be a white lattice quantizer if it satisfies (5) Subtractive dithered quantization (see [15] and [16] is achieved by adding the random variable Z K to every K block of source samples before quantization, and subtracting it at reconstruction. The dither samples are drawn independently for every new K block, and are assumed to be available to the decoder (e.g. the dither comes from a ....

L.G. Roberts. Picture coding using pseudo-random noise. IRE Trans. on Information Theory, IT-8:145--154, 1962.

....on both the lattice and the dither vector. We indicate methods for generating suitable dither vectors for each scheme. 1 Introduction Uniform scalar quantizers have been analyzed in the past [1] using the Fourier series tools. Dithering in uniform scalar quantization was invented by Roberts [2]. The idea was to add some random noise to the input before quantization, and possibly subtract the same noise after the quantization. Accordingly, dithering is classified as subtractive and nonsubractive. The theoretical analysis of dithering goes back to Schuchman [3] although until recently, ....

L. G. Roberts, "Picture coding using pseudorandom noise," IRE Trans. Inform. Theory, vol. IT8, pp. 145-154, Feb. 1962.

.... more complex vector quantization algorithms like the LBG and ECVQ [1] 2] The geometric regularity of lattices allow very fast quantization algorithms, and there are already efficient algorithms for several well known lattice structures [3] 7] Dithering was first applied by Roberts [8] to image coding. It was seen that by adding an independent random variable called dither before the quantization and subtracting after it, the perceptual quality of the image improves substantially. After that pioneering idea, there has been considerable work on the theory and applications of ....

L.G. Roberts, "Picture coding using pseudo-random noise," IRE Trans. Information Theory, vol. IT-8, pp. 145-154, Feb. 1962.

....noise technique. r(k 1 ; k 2 ) is the known pseudorandom noise and the operator Q( Delta) denotes quantization. gives artificial contours in the coarsely quantized image. This artifact is still present in the reconstructed image after the synthesis stage. Roberts pseudo random noise technique [23] can be applied to this subband to avoid this problem. 2.3.2 Roberts Pseudo Random Noise Technique Let us denote x(k 1 ; k 2 ) the image to be quantized. In our case the input image x(k 1 ; k 2 ) is the low frequency subband. Suppose that we have access to a known white noise sequence, r(k 1 ; k ....

L.G. Roberts, "Picture coding using pseudo--random noise", IRE Transactions on information theory, Vol. IT--8, pp. 145--154, Feb. 1962.

No context found.

L. G. Roberts, "Picture coding using pseudo random noise," IRE Transactions on Information Theory, vol. IT-8, pp. 145-154, Feb. 1962.

No context found.

Roberts, L. G., "Picture Coding Using Pseudo-Random Noise," IRE Trans. on Information Theory, Vol. 8, p. 145-154, 1962.

No context found.

G. L. Roberts, "Picture coding using pseudo-random noise," IRE Trans. on Information Theory, vol. IT-8, no. 2, pp. 145--54, Feb 1962.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC