Data-Driven Image Restoration

Every day many images are taken by digital cameras, and people are demanding visually accurate and pleasing result. Noise and blur degrade images captured by modern cameras, and high-level vision tasks (such as segmentation, recognition, and tracking) require high-quality images. Therefore, image restoration specifically, image deblurring and image denoising is a critical preprocessing step. A fundamental problem in image deblurring is to recover reliably distinct spatial frequencies that have been suppressed by the blur kernel. Existing image deblurring techniques often rely on generic image priors that only help recover part of the frequency spectrum, such as the frequencies near the high-end. To this end, we pose the following specific questions: (i) Does class-specific information offer an advantage over existing generic priors for image quality restoration? (ii) If a class-specific prior exists, how should it be encoded into a deblurring framework to recover attenuated image frequencies? Throughout this work, we devise a class-specific prior based on the band-pass filter responses and incorporate it into a deblurring strategy. Specifically, we show that the subspace of band-pass filtered images and their intensity distributions serve as useful priors for recovering image frequencies. Next, we present a novel image denoising algorithm that uses external, category specific image database. In contrast to existing noisy image restoration algorithms, our method selects clean image “support patches” similar to the noisy patch from an external database. We employ a content adaptive distribution model for each patch where we derive the parameters of the distribution from the support patches. Our objective function composed of a Gaussian fidelity term that imposes category specific information, and a low-rank term that encourages the similarity between the noisy and the support patches in a robust manner. Finally, we propose to learn a fully-convolutional network model that consists of a Chain of Identity Mapping Modules (CIMM) for image denoising. The CIMM structure possesses two distinctive features that are important for the noise removal task. Firstly, each residual unit employs identity mappings as the skip connections and receives pre-activated input to preserve the gradient magnitude propagated in both the forward and backward directions. Secondly, by utilizing dilated kernels for the convolution layers in the residual branch, each neuron in the last convolution layer of each module can observe the full receptive field of the first layer

Integrated DC-DC Charger Powertrain Converter Design for Electric Vehicles Using Wide Bandgap Semiconductors

Electric vehicles (EVs) adoption is growing due to environmental concerns, government subsidies, and cheaper battery packs. The main power electronics design challenges for next-generation EV power converters are power converter weight, volume, cost, and loss reduction. In conventional EVs, the traction boost and the onboard charger (OBC) have separate power modules, passives, and heat sinks. An integrated converter, combining and re-using some charging and powertrain components together, can reduce converter cost, volume, and weight. However, efficiency is often reduced to obtain the advantage of cost, volume, and weight reduction.An integrated converter topology is proposed to combine the functionality of the traction boost converter and isolated DC-DC converter of the OBC using a hybrid transformer where the same core is used for both converters. The reconfiguration between charging and traction operation is performed by the existing Battery Management System (BMS) contactors. The proposed converter is operated in both boost and dual active bridge (DAB) mode during traction operation. The loss mechanisms of the proposed integrated converter are modeled for different operating modes for design optimization. An aggregated drive cycle is considered for optimizing the integrated converter design parameters to reduce energy loss during traction operation, weight, and cost. By operating the integrated converter in DAB mode at light-load and boost mode at high-speed heavy-load, the traction efficiency is improved. An online mode transition algorithm is also developed to ensure stable output voltage and eliminate current oscillation during the mode transition. A high-power prototype is developed to verify the integrated converter functionality, validate the loss model, and demonstrate the online transition algorithm. An automated closed-loop controller is developed to implement the transition algorithm which can automatically make the transition between modes based on embedded efficiency mapping. The closed-loop control system also regulates the integrated converter output voltage to improve the overall traction efficiency of the integrated converter. Using the targeted design approach, the proposed integrated converter performs better in all three aspects including efficiency, weight, and cost than comparable discrete solutions for each converter

Contribution of Onion Seed Production to Poverty Reduction: A Case Study of Malakand Division, Pakistan

According to the latest estimates, roughly one-third of the total population of the developing countries live in poverty, majority of which are rural inhabitants (as reported 35 percent of the Pakistani rural mass). In Pakistan, the income distribution has worsened in the rural areas while it has marginally improved in urban areas during the period 1979 through 1996-97 [Pakistan (2001)]. The rural poverty is continuously feeding unemployment through migration of unskilled people to the urban areas. Poverty reduction is a priority area for Pakistan. The government is taking measures for addressing problems of the poor who are the most vulnerable amongst the different socioeconomic groups. Poverty alleviation is the main focus of the government in addition to develop physical infrastructure in rural areas and remove income disparities between income groups and regions. The government of Pakistan has initiated measures to poverty reduction through establishing number of institutions namely Pakistan Poverty Alleviation Fund, Micro-credit Bank (Khushali Bank), Pakistan Baitual Mal, Income Safety Nets, and launching Khushal Pakistan Programme and Food Support Programme. All these programmes are aiming at helping poor and hungry people by providing them food for temporary relief and micro credit for initiating sustainable economic activities. Since the majority of our population is living in rural areas, so the government is diverting more resources to improve the access for rural services and encourage greater participation in economic activities through creating employment opportunities. The programmes in education, health and population sectors have been specifically designed to extend socioeconomic opportunities to rural poor.