An Optimization-Based Approach to Radar Image Reconstruction in Breast Microwave Sensing

Breast microwave sensing (BMS) has been studied as a potential technique for cancer detection due to the observed microwave properties of malignant and healthy breast tissues. This work presents a novel radar-based image reconstruction algorithm for use in BMS that reframes the radar image reconstruction process as an optimization problem. A gradient descent optimizer was used to create an optimization-based radar reconstruction (ORR) algorithm. Two hundred scans of MRI-derived breast phantoms were performed with a preclinical BMS system. These scans were reconstructed using the ORR, delay-and-sum (DAS), and delay-multiply-and-sum (DMAS) beamformers. The ORR was observed to improve both sensitivity and specificity compared to DAS and DMAS. The estimated sensitivity and specificity of the DAS beamformer were 19% and 44%, respectively, while for ORR, they were 27% and 56%, representing a relative increase of 42% and 27%. The DAS reconstructions also exhibited a hot-spot image artifact, where a localized region of high intensity that did not correspond to any physical phantom feature would be present in an image. This artifact appeared like a tumour response within the image and contributed to the lower specificity of the DAS beamformer. This artifact was not observed in the ORR reconstructions. This work demonstrates the potential of an optimization-based conceptualization of the radar image reconstruction problem in BMS. The ORR algorithm implemented in this work showed improved diagnostic performance and fewer image artifacts compared to the widely employed DAS algorithm.

Identifikasi Perubahan Penggunaan Lahan dan Karakteristik Hidrologi DAS Citarum Hulu

The Citarum watershed is one of the priority watersheds due to problems of critical land, flooding, erosion, and sedimentation which continue to increase every year. As the main catchment area that contributes to maintaining the availability of water resources, the upstream Citarum watershed continues to experience a reduction in forest and an increase in built-up land. A research aimed to analyze land use changes to the hydrological characteristics was carried out at the Watershed. The methods used include interpretation of SPOT image data, analysis of land use changes, and determining the values of KRA and KAT. The results of the analysis of land use change conditions in 2009-2018 saw a reduction in forest area (-5.5%), rice fields (-17.4%), and shrubs (-60.8%). Land use increased in built up land (39.7%), dry land agriculture (13%), plantations (6.4%), and open land (95.5%). The highest discharge occurred in 2010 at 606,3 m3/second and the lowest discharge in 2012 was 4,3 m3/second. The KRA and KAT values of the Upper Citarum watershed were moderate and very high. The multiple linear regression model of the relationship between land use changes that affect river flow fluctuations is Y = 2380.5 + 0.9 rainfall -206.5 forest + 6.1 build-up area -31.8 dryland agriculture + e. Other factors that influence the increase in river discharge are the slope of land slopes, rainfall patterns, and inadequate land use methods. Keywords: hydrological characteristics, landuse change, Upper Citarum watershed

Feasibility of Laser Communication Beacon Light Compressed Sensing

The Compressed Sensing (CS) camera can compress images in real time without consuming computing resources. Applying CS theory in the Laser Communication (LC) system can minimize the assumed transmission bandwidth (normally from a satellite to a ground station) and minimize the storage costs of beacon light-spot images; this can save more than ten times the typical bandwidth or storage space. However, the CS compressive process affects the light-spot tracking and key parameters in the images. In this study, we quantitatively explored the feasibility of the CS technique to capture light-spots in LC systems. We redesigned the measurement matrix to adapt to the requirement of light-tracking. We established a succinct structured deep network, the Compressed Sensing Denoising Center Net (CSD-Center Net) for denoising tracking computation from compressed image information. A series of simulations was made to test the performance of information preservation in beacon light spot image storage. With the consideration of CS ratio and application scenarios, coupled with CSD-Center Net and standard centroid, CS can achieve the tracking function well. The information preserved in compressed information correlates with the CS ratio; higher CS ratio can preserve more details. In fact, when the data rate is up than 10%, the accuracy could meet the requirements what we need in most application scenarios.

Tourist Behavior Recognition Through Scenic Spot Image Retrieval Based on Image Processing

The monitoring of tourist behaviors, coupled with the recognition of scenic spots, greatly improves the quality and safety of travel. The visual information is the underlying features of scenic spot images, but the semantics of the information have not been satisfactorily classified or described. Based on image processing technologies, this paper presents a novel method for scenic spot retrieval and tourist behavior recognition. Firstly, the framework of scenic spot image retrieval was constructed, followed by a detailed introduction to the extraction of scale invariant feature transform (SIFT) features. The SIFT feature extraction includes five steps: scale space construction, local space extreme point detection, precise positioning of key points, determination of key point size and direction, and generation of SIFT descriptor. Next, multiple correlated images were mined for the target scenic spot image, and the feature matching method between the target image and the set of scenic spot images was introduced in details. On this basis, a tourist behavior recognition method was designed based on temporal and spatial consistency. The proposed method was proved effective through experiments. The research results provide theoretical reference for image retrieval and behavior recognition in many other fields.

Laser Spot Center Location Method for Chinese Spaceborne GF-7 Footprint Camera

The Gaofen-7 (GF-7) satellite is equipped with two area array sensor footprint cameras to capture the laser altimeter spot. In order to establish a direct correspondence between the laser data and the stereo image data, a new method is proposed to fit the center of the spot using the brightness difference between the spot image and the footprint image. First, the geometric registration between the spot image and the footprint image is completed based on feature matching or template matching. Then, the brightness values between the two images are extracted from the corresponding image position to form a measurement, and the least squares adjustment method is used to calculate the parameters of the brightness conversion model between the spot image and the footprint image. Finally, according to the registration relationship, the center of the identified spots is respectively positioned in the footprint images, so that the laser spots are accurately identified in the along-track stereo footprint images. The experimental results show that the spot error of this method is less than 0.7 pixel, which has higher reliability and stability, and can be used for a GF-7 satellite footprint camera.

Decoupling of the position and angular errors in laser pointing with a neural network method

In laser-pointing-related applications, when only the centroid of a laser spot is considered, then the position and angular errors of the laser beam are often coupled together. In this study, the decoupling of the position and angular errors is achieved from one single spot image by utilizing a neural network technique. In particular, the successful application of the neural network technique relies on novel experimental procedures, including using an appropriate small-focal-length lens and tilting the detector, to physically enlarge the contrast of different spots. This technique, with the corresponding new system design, may prove to be instructive in the future design of laser-pointing-related systems.