Abstract We propose a new small target detection system that detects small target candidates based on morphology operations and detects actual targets using a modified Gaussian distance function. To reduce clutter on the edges of clouds, a median filter is applied as preprocessing. Two kinds of images are calculated with closing and opening morphological operators, respectively. In the morphology operations, various sizes of structure elements that are used to consider the sizes of targets and candidate targets are extracted from different images between the two images in the closing and opening operations. With a modified Gaussian distance function, small targets are detected from the candidate targets. The proposed method is less sensitive to clutters than existing methods and has a detection rate of 98%. Copyright © 2014 John Wiley & Sons, Ltd.

UNLABELLED: NoRSE was developed to analyze high-frequency datasets collected from multistate, dynamic experiments, such as molecular adsorption and desorption onto carbon nanotubes. As technology improves sampling frequency, these stochastic datasets become increasingly large with faster dynamic events. More efficient algorithms are needed to accurately locate the unique states in each time trace. NoRSE adapts and optimizes a previously published noise reduction algorithm and uses a custom peak flagging routine to rapidly identify unique event states. The algorithm is explained using experimental data from our lab and its fitting accuracy and efficiency are then shown with a generalized model of stochastic datasets. The algorithm is compared to another recently published state finding algorithm and is found to be 27 times faster and more accurate over 55% of the generalized experimental space. NoRSE is written as an M-file for Matlab. AVAILABILITY: http://web.mit.edu/stranogroup/NoRSE.txt.

The recent H.264/AVC video coding standard provides a higher coding efficiency than previous standards. H.264/AVC achieves a bit rate saving of more than 50 % with many new technologies, but it is computationally complex. Most of fast mode decision algorithms have focused on Baseline profile of H.264/AVC which does not consider B-picture coding. In this paper, a fast block mode decision scheme for B-pictures in High profile and Main profile is proposed to reduce the computational complexity for H.264/AVC. To reduce the block mode decision complexity in B-pictures of High profile, we use the SAD value after 16×16 block motion estimation. This SAD value is used for the classification feature to divide all block modes into some proper candidate search block modes. A differential mode allocation method is also used for the list (list 0, list 1) of B-slices based on the SAD value of the 16 × 16 block mode. The proposed algorithm shows the average speed-up factors of 41.9 ∼ 58.57% for IBBPBB sequences with a negligible bit increment and a minimal loss of image quality.

In this paper, a rate-distortion optimized variable block transform coding scheme is proposed based on a hierarchical structured transform for macroblock (MB) coding with a set of the order-4 and −8 integer cosine transform (ICT) kernels of H.264/AVC as well as a new order-16 ICT kernel. The set of order-4, −8 and −16 ICT kernels are applied for inter-predictive coding in square (4×4, 8×8 or 16×16) or non-square (16×8 or 8×16) transform for each MB in a hierarchical structured manner. The proposed hierarchical variable-sized block transform scheme using the order-16 ICT kernel achieves significant bitrate reduction up to 15%, compared to the High profile of H.264/AVC. Even if the number of candidates for the transform types increases, the encoding time can be reduced to average 4–6% over the H.264/AVC

An efficient intra mode decision scheme is proposed to reduce the computational complexity of inter frame coding in for the H.264/AVC. To decrease this computational burden, we propose an adaptive thresholding method based on distribution characteristics of the sum of the absolute differences (SAD) for the best inter mode when the intra mode is the final coding mode. We also include a simple refinement process by using spatial correlation between neighbouring marcoblocks (MBs) and the current MB. The performance of the proposed scheme is presented in terms of reduction in encoding times and PSNR values, and the increments in bit amounts.

Block motion estimation with full search is computationally complex. To reduce this complexity, different methods have been proposed, including partial distortion, which can reduce the computational complexity with no loss of image quality. We propose a distortion-based partial distortion search (DPDS) based on the magnitude of distortion and adaptive update of the matching order. We calculate absolute differences for all pixels in the predicted block point. Pixels are then sorted by the amount of distortion in a descending order for the matching process, which produces a scanning map. The sum of the absolute differences (SAD) of other candidate positions is then computed from this matching order. We also use an update of the scanning map by checking the increase in the number of absolute differences for the SAD value. The proposed DPDS algorithm improves the computational efficiency, compared with the original PDS scheme, because the accumulated value of the absolute pixel differences can rapidly reach the current minimum SAD value. The proposed algorithm is 4-13 times faster than the full search method with the same visual quality.

We propose a simple fast block-matching algorithm (BMA) based on the direction of the predicted motion vector called directional & adaptive diamond search by adaptive pattern switching (DADS-APS). The proposal method has two sequential search steps, including 1) an initial search, and 2) a refinement search for the local area. Adaptive pattern switching (APS) is proposed for the initial search and a unit-size rood pattern is used for the refinement. The initial search step consists of pattern size determination and selection of a pattern shape. We use an adaptive pattern size that is adjusted by the amount of motion. This method is superior to a fixed-pattern size algorithm, regardless of the amount of motion. In video sequences, each motion has a unique direction. using this property, we use adaptive pattern switching between ARPS and DADS. APS considers the motion direction so we can easily and correctly find the minimal matching error (MME) point with less error distortion. APS can thus reduce the number of poorly related search points. Analysis shows that DADS-APS exhibits good PSNR performance and the average number of search points compares favorably with other methods.

This paper describes a design of a tactile sensor, which can measure three components forces. The bio-mimetic tactile sensor, alternative to human’s finger, is composed of 100 micro force sensors, and its size being 10 mm x 10 mm. Each micro force sensor has a square membrane, and its force capacity is 0.3 N in the three-axis directions. On the other hand, the measuring method of three-component force signals without interference was suggested in case of four strain gages and the number of minimum data lines. We have fabricated the tactile sensor using flexible MEMS technology based on polymer material.