Improved bounds for the rate loss of multiresolution source codes

We present new bounds for the rate loss of multiresolution source codes (MRSCs). Considering an M-resolution code, the rate loss at the ith resolution with distortion D/sub i/ is defined as L/sub i/=R/sub i/-R(D/sub i/), where R/sub i/ is the rate achievable by the MRSC at stage i. This rate loss describes the performance degradation of the MRSC compared to the best single-resolution code with the same distortion. For two-resolution source codes, there are three scenarios of particular interest: (i) when both resolutions are equally important; (ii) when the rate loss at the first resolution is 0 (L/sub 1/=0); (iii) when the rate loss at the second resolution is 0 (L/sub 2/=0). The work of Lastras and Berger (see ibid., vol.47, p.918-26, Mar. 2001) gives constant upper bounds for the rate loss of an arbitrary memoryless source in scenarios (i) and (ii) and an asymptotic bound for scenario (iii) as D/sub 2/ approaches 0. We focus on the squared error distortion measure and (a) prove that for scenario (iii) L/sub 1/<1.1610 for all D/sub 2/<0.7250; (c) tighten the Lastras-Berger bound for scenario (i) from L/sub i//spl les/1/2 to L/sub i/<0.3802, i/spl isin/{1,2}; and (d) generalize the bounds for scenarios (ii) and (iii) to M-resolution codes with M/spl ges/2. We also present upper bounds for the rate losses of additive MRSCs (AMRSCs). An AMRSC is a special MRSC where each resolution describes an incremental reproduction and the kth-resolution reconstruction equals the sum of the first k incremental reproductions. We obtain two bounds on the rate loss of AMRSCs: one primarily good for low-rate coding and another which depends on the source entropy

On the rate loss and construction of source codes for broadcast channels

In this paper, we first define and bound the rate loss of source codes for broadcast channels. Our broadcast channel model comprises one transmitter and two receivers; the transmitter is connected to each receiver by a private channel and to both receivers by a common channel. The transmitter sends a description of source (X, Y) through these channels, receiver 1 reconstructs X with distortion D1, and receiver 2 reconstructs Y with distortion D2. Suppose the rates of the common channel and private channels 1 and 2 are R0, R1, and R2, respectively. The work of Gray and Wyner gives a complete characterization of all achievable rate triples (R0,R1,R2) given any distortion pair (D1,D2). In this paper, we define the rate loss as the gap between the achievable region and the outer bound composed by the rate-distortion functions, i.e., R0+R1+R2 ≥ RX,Y (D1,D2), R0 + R1 ≥ RX(D1), and R0 + R2 ≥ RY (D2). We upper bound the rate loss for general sources by functions of distortions and upper bound the rate loss for Gaussian sources by constants, which implies that though the outer bound is generally not achievable, it may be quite close to the achievable region. This also bounds the gap between the achievable region and the inner bound proposed by Gray and Wyner and bounds the performance penalty associated with using separate decoders rather than joint decoders. We then construct such source codes using entropy-constrained dithered quantizers. The resulting implementation has low complexity and performance close to the theoretical optimum. In particular, the gap between its performance and the theoretical optimum can be bounded from above by constants for Gaussian sources

On the rate-distortion performance and computational efficiency of the Karhunen-Loeve transform for lossy data compression

We examine the rate-distortion performance and computational complexity of linear transforms for lossy data compression. The goal is to better understand the performance/complexity tradeoffs associated with using the Karhunen-Loeve transform (KLT) and its fast approximations. Since the optimal transform for transform coding is unknown in general, we investigate the performance penalties associated with using the KLT by examining cases where the KLT fails, developing a new transform that corrects the KLT's failures in those examples, and then empirically testing the performance difference between this new transform and the KLT. Experiments demonstrate that while the worst KLT can yield transform coding performance at least 3 dB worse than that of alternative block transforms, the performance penalty associated with using the KLT on real data sets seems to be significantly smaller, giving at most 0.5 dB difference in our experiments. The KLT and its fast variations studied here range in complexity requirements from O(n^2) to O(n log n) in coding vectors of dimension n. We empirically investigate the rate-distortion performance tradeoffs associated with traversing this range of options. For example, an algorithm with complexity O(n^3/2) and memory O(n) gives 0.4 dB performance loss relative to the full KLT in our image compression experiment

On the rate loss of multiple description source codes

The rate loss of a multiresolution source code (MRSC) describes the difference between the rate needed to achieve distortion D/sub i/ in resolution i and the rate-distortion function R(D/sub i/). This paper generalizes the rate loss definition to multiple description source codes (MDSCs) and bounds the MDSC rate loss for arbitrary memoryless sources. For a two-description MDSC (2DSC), the rate loss of description i with distortion D/sub i/ is defined as L/sub i/=R/sub i/-R(D/sub i/), i=1,2, where R/sub i/ is the rate of the ith description; the joint rate loss associated with decoding the two descriptions together to achieve central distortion D/sub 0/ is measured either as L/sub 0/=R/sub 1/+R/sub 2/-R(D/sub 0/) or as L/sub 12/=L/sub 1/+L/sub 2/. We show that for any memoryless source with variance /spl sigma//sup 2/, there exists a 2DSC for that source with L/sub 1//spl les/1/2 or L/sub 2//spl les/1/2 and a) L/sub 0//spl les/1 if D/sub 0//spl les/D/sub 1/+D/sub 2/-/spl sigma//sup 2/, b) L/sub 12//spl les/1 if 1/D/sub 0//spl les/1/D/sub 1/+1/D/sub 2/-1//spl sigma//sup 2/, c) L/sub 0//spl les/L/sub G0/+1.5 and L/sub 12//spl les/L/sub G12/+1 otherwise, where L/sub G0/ and L/sub G12/ are the joint rate losses of a Gaussian source with variance /spl sigma//sup 2/

Separable Karhunen Loeve transforms for the weighted universal transform coding algorithm

The weighted universal transform code (WUTC) is a two-stage transform code that replaces JPEG's single, non-optimal transform code with a jointly designed collection of transform codes to achieve good performance across a broader class of possible sources. Unfortunately, the performance gains of WUTC are achieved at the expense of significant increases in computational complexity and larger codes. We here present a faster, more space-efficient WUTC algorithm. The new algorithm uses separable coding instead of direct KLT. While separable coding gives performance comparable to that of WUTC, it uses only 1/8 of the floating-point multiplications and 1/32 of storage of direct KLT. Experimental results included in this work compare the performance of new separable WUTC with both the WUTC and other fast variations of that algorithm

Suboptimality of the Karhunen-Loève transform for transform coding

We examine the performance of the Karhunen-Loeve transform (KLT) for transform coding applications. The KLT has long been viewed as the best available block transform for a system that orthogonally transforms a vector source, scalar quantizes the components of the transformed vector using optimal bit allocation, and then inverse transforms the vector. This paper treats fixed-rate and variable-rate transform codes of non-Gaussian sources. The fixed-rate approach uses an optimal fixed-rate scalar quantizer to describe the transform coefficients; the variable-rate approach uses a uniform scalar quantizer followed by an optimal entropy code, and each quantized component is encoded separately. Earlier work shows that for the variable-rate case there exist sources on which the KLT is not unique and the optimal quantization and coding stage matched to a "worst" KLT yields performance as much as 1.5 dB worse than the optimal quantization and coding stage matched to a "best" KLT. In this paper, we strengthen that result to show that in both the fixed-rate and the variable-rate coding frameworks there exist sources for which the performance penalty for using a "worst" KLT can be made arbitrarily large. Further, we demonstrate in both frameworks that there exist sources for which even a best KLT gives suboptimal performance. Finally, we show that even for vector sources where the KLT yields independent coefficients, the KLT can be suboptimal for fixed-rate coding

Multiresolution source coding using entropy constrained dithered scalar quantization

In this paper, we build multiresolution source codes using entropy constrained dithered scalar quantizers. We demonstrate that for n-dimensional random vectors, dithering followed by uniform scalar quantization and then by entropy coding achieves performance close to the n-dimensional optimum for a multiresolution source code. Based on this result, we propose a practical code design algorithm and compare its performance with that of the set partitioning in hierarchical trees (SPIHT) algorithm on natural images

Multiplicity of Positive Solutions for a Singular Second-Order Three-Point Boundary Value Problem with a Parameter

This paper is concerned with the following second-order three-point boundary value problem u″t+β2ut+λqtft,ut=0, t∈0 , 1, u0=0, u(1)=δu(η), where β∈(0,π/2), δ>0, η∈(0,1), and λ is a positive parameter. First, Green’s function for the associated linear boundary value problem is constructed, and then some useful properties of Green’s function are obtained. Finally, existence, multiplicity, and nonexistence results for positive solutions are derived in terms of different values of λ by means of the fixed point index theory

Rate loss of network source codes

In this thesis, I present bounds on the performance of a variety of network source codes. These rate loss bounds compare the rates achievable by each network code to the rate-distortion bound R(D) at the corresponding distortions. The result is a collection of optimal performance bounds that are easy to calculate. I first present new bounds for the rate loss of multi-resolution source codes (MRSCs). Considering an M-resolution code with M>=2, the rate loss at the ith resolution with distortion D_i is defined as L_i=R_i-R(D_i), where R_i is the rate achievable by the MRSC at stage i. For 2-resolution codes, there are three scenarios of particular interest: (i) when both resolutions are equally important; (ii) when the rate loss at the first resolution is 0 (L_1=0); (iii) when the rate loss at the second resolution is 0 (L_2=0). The work of Lastras and Berger gives constant upper bounds for the rate loss in scenarios (i) and (ii) and an asymptotic bound for scenario (iii). In this thesis, I show a constant bound for scenario (iii), tighten the bounds for scenario (i) and (ii), and generalize the bound for scenario (ii) to M-resolution greedy codes. I also present upper bounds for the rate losses of additive MRSCs (AMRSCs), a special MRSC. I obtain two bounds on the rate loss of AMRSCs: one primarily good for low rate coding and another which depends on the source entropy. I then generalize the rate loss definition and present upper bounds for the rate losses of multiple description source codes. I divide the distortion region into three sub-regions and bound the rate losses by small constants in two sub-regions and by the joint rate losses of a normal source with the same variance in the other sub-region. Finally, I present bounds for the rate loss of multiple access source codes (MASCs). I show that lossy MASCs can be almost as good as codes based on joint source encoding