Systems and methods in accordance with embodiments of the invention are configured to render images using light field image files containing an image synthesized from light field image data and metadata describing the image that includes a depth map. One embodiment of the invention includes a processor and memory containing a rendering application and a light field image file including an encoded image and metadata describing the encoded image, where the metadata comprises a depth map that specifies depths from the reference viewpoint for pixels in the encoded image. In addition, the rendering application configures the processor to: locate the encoded image within the light field image file; decode the encoded image; locate the metadata within the light field image file; and post process the decoded image by modifying the pixels based on the depths indicated within the depth map to create a rendered image.

Systems and methods for decoding light field image files

Systems and methods for transmitting and receiving image data captured by an imager array including a plurality of focal planes are described. One embodiment of the invention includes capturing image data using a plurality of active focal planes in a camera module, where an image is formed on each active focal plane by a separate lens stack, generating lines of image data by interleaving the image data captured by the plurality of active focal planes, and transmitting the lines of image data and the additional data.

Systems and methods for transmitting and receiving array camera image data

Systems and methods for the synthesis of light field images from virtual viewpoints in accordance with embodiments of the invention are disclosed. In one embodiment of the invention, a system includes a processor and a memory configured to store captured light field image data and an image manipulation application, wherein the captured light field image data includes image data, pixel position data, and a depth map, and wherein the image manipulation application configures the processor to obtain captured light field image data, determine a virtual viewpoint for the captured light field image data, where the virtual viewpoint includes a virtual location and virtual depth information, compute a virtual depth map based on the captured light field image data and the virtual viewpoint, and generate an image from the perspective of the virtual viewpoint based on the captured light field image data and the virtual depth map.

Generating Images from Light Fields Utilizing Virtual Viewpoints

Systems and methods for extended color processing on Pelican array cameras in accordance with embodiments of the invention are disclosed. In one embodiment, a method of generating a high resolution image includes obtaining input images, where a first set of images includes information in a first band of visible wavelengths and a second set of images includes information in a second band of visible wavelengths and non-visible wavelengths, determining an initial estimate by combining the first set of images into a first fused image, combining the second set of images into a second fused image, spatially registering the fused images, denoising the fused images using bilateral filters, normalizing the second fused image in the photometric reference space of the first fused image, combining the fused images, determining a high resolution image that when mapped through a forward imaging transformation matches the input images within at least one predetermined criterion.

Extended Color Processing on Pelican Array Cameras

Imager arrays, array camera modules, and array cameras in accordance with embodiments of the invention utilize pixel apertures to control the amount of aliasing present in captured images of a scene. One embodiment includes a plurality of focal planes, control circuitry configured to control the capture of image information by the pixels within the focal planes, and sampling circuitry configured to convert pixel outputs into digital pixel data. In addition, the pixels in the plurality of focal planes include a pixel stack including a microlens and an active area, where light incident on the surface of the microlens is focused onto the active area by the microlens and the active area samples the incident light to capture image information, and the pixel stack defines a pixel area and includes a pixel aperture, where the size of the pixel apertures is smaller than the pixel area.

Systems and methods for controlling aliasing in images captured by an array camera for use in super resolution processing using pixel apertures

Provided are an apparatus and method for processing a light field image that is acquired and processed using a mask to spatially modulate a light field. The apparatus includes a lens, a mask to spatially modulate 4D light field data of a scene passing through the lens to include wideband information on the scene, a sensor to detect a 2D image corresponding to the spatially modulated 4D light field data, and a data processing unit to recover the 4D light field data from the 2D image to generate an all-in-focus image.

Apparatus and method for processing light field data using a mask with an attenuation pattern

Purpose: To understand key meteorological parameters that influence the spread of COVID-19 in Mumbai, India (based on data from April 2020 - April 2021). Methods: The meteorological parameters chosen were Temperature, Dew Temperature, Humidity, Pressure, Wind Speed. The underlying basic relationships between meteorological parameters and COVID-19 information for Mumbai was understood using Spearman's rank correlation coefficients. After establishing basic relationships, Linear analysis and Generalized Additive Model's (GAM) were used to figure out statistically significant weather parameters and model them to explain the best possible variance in the pandemic data. Results: A model of temperature and windspeed could explain 17.3% and 8.3% of variance in Daily new cases and Daily recoveries respectively. As for deaths occurring due to the virus, a model comprising of only pressure best explains a variance of 17.3% in the data. Non-Linear modelling based on GAM confirms the findings of linear analysis and establishes certain non-linear relationships as well. Conclusion: SARS-CoV-2 belongs to the class of Human Coronaviruses (HCoV) which show seasonality depending on weather conditions. The above article focuses on understanding the underlying relationships between SARS-CoV-2 and meteorological parameters that would help progress basic research and formulation of policies around the disease for each weather/season.

Impact of key meteorological parameters on the spread of COVID-19 in Mumbai: Correlation and Regression Analysis

The proposed system acquires and transfers data from a vehicle's analog and digital sensors to the user's very own mobile phone. The device uses a microcontroller to accept the sensor inputs and generate an audio signal indicative of the data acquired by the sensors and an audio jack which on inserting into the phone acts as a channel to transfer the data collected by the sensors to the cell phone. This data acquired from the sensors is fed to the microphone jack of the cell phone which is then processed by a mobile application and decoded sensor values are displayed on the cell phone. The ultra-low cost nature of the technology enables new additional applications like: On-The-Spot Soil Testing, Home Automation, Traffic Data Capture and Health Data Capture, etc. at disruptive prices.

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Ultra-low cost vehicle data acquisition and transfer system from analog and digital sensors to audio channel of a phone

Computational photography involves sophisticated capture methods. A new trend is to capture projection of higher dimensional visual signals such as videos, multi-spectral data and lightfields on lower dimensional sensors. Carefully designed capture methods exploit the sparsity of the underlying signal in a transformed domain to reduce the number of measurements and use an appropriate reconstruction method. Traditional progressive methods may capture successively more detail using a sequence of simple projection basis, such as DCT or wavelets and employ straightforward backprojection for reconstruction. Randomized projection methods do not use any specific sequence and use L0 minimization for reconstruction. In this paper, we analyze the statistical properties of natural images, videos, multi-spectral data and light-fields and compare the effectiveness of progressive and random projections. We define effectiveness by plotting reconstruction SNR against compression factor. The key idea is a procedure to measure best-case effectiveness that is fast, independent of specific hardware and independent of the reconstruction procedure. We believe this is the first empirical study to compare different lossy capture strategies without the complication of hardware or reconstruction ambiguity. The scope is limited to linear non-adaptive sensing. The results show that random projections produce significant advantages over other projections only for higher dimensional signals, and suggest more research to nascent adaptive and non-linear projection methods.

Rohit Pandharkar

Papers

Apparatus and method for processing light field data using a mask with an attenuation pattern

Impact of key meteorological parameters on the spread of COVID-19 in Mumbai: Correlation and Regression Analysis

Ultra-low cost vehicle data acquisition and transfer system from analog and digital sensors to audio channel of a phone

Progressive versus Random Projections for Compressive Capture of Images, Lightfields and Higher Dimensional Visual Signals