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Convolutional networks have been widely used for the classification of hyperspectral images; however, such networks are notorious for their large number of trainable parameters and high computational complexity. Additionally, traditional convolution-based methods are typically implemented as a simple cascade of a number of convolutions using a single-scale convolution kernel. In contrast, a lightweight multiscale convolutional network is proposed, capitalizing on feature extraction at multiple scales in parallel branches followed by feature fusion. In this approach, 2-D depthwise convolution is used instead of conventional convolution to reduce network complexity without sacrificing classification accuracy. Furthermore, multiscale channel attention (MSCA) is also employed to selectively exploit discriminative capability across various channels. To do so, multiple 1-D convolutions with varying kernel sizes provide channel attention at multiple scales, again with the goal of minimizing network complexity. Experimental results reveal that the proposed network not only outperforms other competing lightweight classifiers in terms of classification accuracy, but also exhibits a lower number of parameters as well as significantly less computational cost. [ABSTRACT FROM AUTHOR]

The performance advantage of redundant wavelet multihypothesis (RWMH) for motion compensation in video coding over single-hypothesis techniques is analyzed, and a derivation that quantifies the gain of RWMH over single-phase prediction under a partitioning model is presented. The RWMH technique substantially reduces the variance of the prediction residual leading to higher coding efficiency and is effective for a block-based implementation.

Multihypothesis with phase diversity is introduced into motion-compensated temporal filtering by deploying the latter in the domain of a spatially redundant wavelet transform. The centerpiece of this redundant-wavelet approach to multihypothesis temporal filtering is a multiple-phase inverse transform that involves an implicit projection significantly reducing noise not captured by the motion model of the temporal filtering. The primary contribution of the work is a derivation that establishes analytically the advantage of the redundant-wavelet approach as compared to equivalent temporal filtering taking place in the spatial domain. For practical implementation, a regular triangle mesh is used to track motion between frames, and an affine transform between mesh triangles implements motion compensation within a lifting-based temporal transform. Experimental results reveal that the incorporation of phase-diversity multihypothesis into motion-compensated temporal filtering improves rate-distortion performance, and state-of-the-art scalable performance is observed. Index Terms--Motion-compensated temporal filtering (MCTF), multihypothesis motion compensation, redundant wavelet transform, scalable video coding.

Geoscience applications often produce sizable datasets that are vector-valued and increasingly in need of compression algorithms to reduce storage and transmission burdens, particularly when the data are time-varying. In this paper, several advanced interframe-compression techniques are extended from the traditional realm of natural video to the coding of time-varying vector fields. Although similar to natural video in some respects, time-varying vector-field sequences often possess complex temporal evolution of vector-valued features that are important to the analytic quality of the data yet defy the simple motion models widely employed for natural video. To improve coding performance, motion compensation with reduced resolution is proposed such that motion compensation is applied only at low spatial resolution, while high-resolution information, for which the motion model fails, is intraframe coded with no temporal decorrelation. In empirical results on datasets of ocean-surface winds, this reduced-resolution motion-compensation technique results in significant performance improvement and greater feature preservation. Index Terms--Motion compensation, time-varying vector fields, vector-valued data compression, vector wavelet transform.

It is shown that most existing multiwavelets perform poorly when used to implement vector wavelet transforms (VWT). Incorporation of a new crierion in the multiwavelet-design procedure can remedy this, relying on multiwavelets that are balanced in an omnidirectional sense.

Our high technology society Continues to rely more and more upon sophisticated measurements, technical standards, and associated testing activities. This was true for the industrial society of the 20th century […]

A mathematical definition of adaptive vector quantization (AVQ) is outlined, describing the structure of AVQ communication systems. A new AVQ algorithm, generalized threshold replenishment (GTR) is described. GTR is an online algorithm not dependent on substantial buffering or iterative processing. It outperforms other AVQ algorithms due to its simultaneous consideration of rate and distortion.

This paper describes a differential-vector-quantization (DVQ) algorithm that has been developed for real-time compression of digital video images. We discuss a number of experiments performed to insure that the algorithm is suitable for hardware implementation. We show that the DVQ algorithm performs comparably to scalar differential-pulse-code-modulation (DPCM) methods in terms of image quality and compression. We also show that the DVQ algorithm is much more robust in the presence of channel noise than alternatives employing variable-length encoding.

Reflectance data are often preferred to radiance data in applications of multispectral and hyperspectral imagery in which subtle spectral features are analyzed. In such applications, atmospheric correction, the process which provides radiance-to-reflectance conversion, plays a prominent role in the data-distribution and archiving pipeline. Lossy compression, often in the form of the JPEG2000 standard, will also likely factor into the distribution and archiving data flow. The relative position of data compression with respect to atmospheric correction is considered and evaluated with experimental results on both multispectral and hyperspectral imagery, and recommendations on an appropriate order for compression in the data-flow chain are made. Index Terms--Atmospheric correction, data compression, hyperspectral imagery, multispectral imagery.

We describe the wavelets around land masses (WAVAL) system for the embedded coding of three-dimensional (3-D) oceanographic images. These images differ from those arising in other applications in that valid data exists only at grid points corresponding to sea. Grid points that cover land or lie beyond the bathymetry have no associated data. For these images, the WAVAL system employs a 3.D lifting wavelet transform tailored specifically to the potentially sparse nature of the data by processing only the valid sea data points between land masses. We introduce successive-approximation runlength (SARL) coding, an embedded-coding procedure that adds successive-approximation properties to the well known stack-run (SR) algorithm. SARL is employed to code wavelet coefficients resulting from the 3-D transform in the WAVAL system. However, it is a general technique applicable to other coding tasks in which embedded coding is desired but for which zerotree techniques are impractical. Experimental results show that the WAVAL system achieves substantial improvement in rate-distortion performance over the technique currently used by the U.S. Navy for compression of oceanographic imagery. Index Terms--Embedded coding, three-dimensional data compression, wavelet-based compression.

A new system for intraframe coding of video is described. This system combines zerotrees of vectors of wavelet coefficients and the generalized-threshold-replenishment (GTR) technique for adaptive vector quantization (AVQ). A data structure, the vector zerotree (VZT), is introduced to identify trees of insignificant vectors, i.e., those vectors of wavelet coefficients in a dyadic subband decomposition that are to be coded as zero. GTR coders are then applied to each subband to efficiently code the significant vectors by way of adapting to their changing statistics. Both VZT generation and GTR coding are based upon minimization of criteria involving both rate and distortion. In addition, perceptual performance is improved by invoking simple, perceptually motivated weighting in both the VZT and the GTR coders. Our experimental findings indicate that the described VZTGTR system handles dramatic changes in image statistics, such as those due to a scene change, more efficiently than wavelet-based techniques employing nonadaptive scalar quantizers. Index Terms--Adaptive vector quantization, image-sequence coding, zerotree coding.