Fourier tabanlı optik modülasyon ile tek çekimde alt-pozlama görüntülerinin çıkarılması

Through pixel-wise optical coding of images during exposure time, it is possible to extract sub-exposure images from a single capture. Such a capability can be used for different purposes, including high-speed imaging, high-dynamic-range imaging and compressed sensing. Here, we demonstrate a sub-exposure image extraction method, where the exposure coding pattern is inspired from frequency division multiplexing idea of communication systems. The coding masks modulate subexposure images in such a way that they are placed in non-overlapping regions in Fourier domain. The sub-exposure image extraction process involves digital filtering of the captured signal with proper band-pass filters. The prototype imaging system incorporates a Liquid Crystal over Silicon (LCoS) based spatial light modulator synchronized with a camera for pixel-wise exposure coding.Pozlama süresinde piksellerin optik olarak kodlanması vasıtasıyla, tek bir görüntü kaydından birden çok alt-pozlama görüntüsünün elde edilmesi mümkündür. Böyle bir kabiliyet; yüksek hızlı görüntüleme, yüksek dinamik aralıklı görüntüleme ve sıkıştırılmış görüntüleme gibi çeşitli amaçlar için kullanılabilir. Bu tezde, kodlama örüntüsünün haberleşme sistemlerinde kullanılan "frekans bölüşümlü çoğullama" fikrinden esinlenildiği bir alt-pozlama görüntüsü elde etme metodu sunulmaktadır. Bu metodda; optik maskeler, alt-pozlama görüntülerini Fourier uzayında örtüşmeyecek şekilde yerleştirilmesini sağlayacak şekilde tasarlanmıştır. Alt-pozlama görüntüleri, kaydedilmiş sinyalin uygun şekilde bant-geçiren filtrelerden geçirilmesiyle elde edilmektedir. Prototip görüntüleme sistemi; piksel bazlı kodlama için Liquid Crystal over Silicon (LCoS) teknolojisine dayalı bir uzamsal ışık modülatörü ile senkronize edilmiş bir kamera vasıtasıya gerçekleştirilmiştir

Efficient Space-Time Sampling with Pixel-wise Coded Exposure for High Speed Imaging

Cameras face a fundamental tradeoff between spatial and temporal resolution. Digital still cameras can capture images with high spatial resolution, but most high-speed video cameras have relatively low spatial resolution. It is hard to overcome this tradeoff without incurring a significant increase in hardware costs. In this paper, we propose techniques for sampling, representing and reconstructing the space-time volume in order to overcome this tradeoff. Our approach has two important distinctions compared to previous works: (1) we achieve sparse representation of videos by learning an over-complete dictionary on video patches, and (2) we adhere to practical hardware constraints on sampling schemes imposed by architectures of current image sensors, which means that our sampling function can be implemented on CMOS image sensors with modified control units in the future. We evaluate components of our approach - sampling function and sparse representation by comparing them to several existing approaches. We also implement a prototype imaging system with pixel-wise coded exposure control using a Liquid Crystal on Silicon (LCoS) device. System characteristics such as field of view, Modulation Transfer Function (MTF) are evaluated for our imaging system. Both simulations and experiments on a wide range of scenes show that our method can effectively reconstruct a video from a single coded image while maintaining high spatial resolution

Compressive Holographic Video

Compressed sensing has been discussed separately in spatial and temporal domains. Compressive holography has been introduced as a method that allows 3D tomographic reconstruction at different depths from a single 2D image. Coded exposure is a temporal compressed sensing method for high speed video acquisition. In this work, we combine compressive holography and coded exposure techniques and extend the discussion to 4D reconstruction in space and time from one coded captured image. In our prototype, digital in-line holography was used for imaging macroscopic, fast moving objects. The pixel-wise temporal modulation was implemented by a digital micromirror device. In this paper we demonstrate $10\times$ temporal super resolution with multiple depths recovery from a single image. Two examples are presented for the purpose of recording subtle vibrations and tracking small particles within 5 ms.Comment: 12 pages, 6 figure

SmartPIV: flow velocity estimates by smartphones for education and field studies

In this paper, a smartphone application is presented that was developed to lower the barrier to introduce particle image velocimetry (PIV) in lab courses. The first benefit is that a PIV system using smartphones and a continuous wave (cw-) laser is much cheaper than a conventional system and thus much more affordable for universities. The second benefit is that the design of the menus follows that of modern camera apps, which are intuitively used. Thus, the system is much less complex and costly than typical systems, and our experience showed that students have much less reservations to work with the system and to try different parameters. Last but not least the app can be applied in the field. The relative uncertainty was shown to be less than 8%, which is reasonable for quick velocity estimates. An analysis of the computational time necessary for the data evaluation showed that with the current implementation the app is capable of providing smooth live display vector fields of the flow. This might further increase the use of modern measurement techniques in industry and education