The spike trains of retinal ganglion cells (RGCs) are the only source of visual information to the brain. Here, we genetically identify an RGC type in mice that functions as a pixel encoder and increases firing to light increments (PixON-RGC). PixON-RGCs have medium-sized dendritic arbors and non-canonical center-surround receptive fields. From their receptive field center, PixON-RGCs receive o...

Image segmentation is an essential processing step for many image analysis applications. We propose a novel pixon-based adaptive scale method for image segmentation. The key idea of our approach is that a pixon-based image model is combined with a Markov random field (MRF) model under a Bayesian framework. We introduce a new pixon scheme that is more suitable for image segmentation than the "fu...

This lecture introduces pixon-based image restoration/reconstruction methods. The relationship between image Algorithmic Information Content and the Bayesian incarnation of Occam's Razor are discussed as well as the relationship of multiresolution pixon languages and image fractal dimension. Also discussed is the relationship of pixons to the role played by the Heisenberg uncertainty principle ...

Image segmentation, which is an important stage of many image processing algorithms, is the process of partitioning an image into nonintersecting regions, such that each region is homogeneous and the union of no two adjacent regions is homogeneous. This paper presents a novel pixon-based algorithm for image segmentation. The key idea is to create a pixon model by combining fuzzy filtering as a ...

Pixon noise reduction was applied to 18 planar images, six each from 99mTc-methylene diphosphonate (99mTc-MDP), 67Ga citrate (67Ga), and (123)I-metaiodobenzylguanidine ((123)I-MIBG) studies. Pixon processing increased patient signal-to-noise ratio, 6.8-11.8 fold. Three specialists preferred processed images 44 of 54 times with good agreement (87%). Most (9/10, p<0.02) of the null and negative p...

This paper reviews pixon-based image reconstruction, which in it current formulation uses a multiresolution language to quantify an image's Algorithmic Information Content (AIC) using Baye-sian techniques. Each pixon (or its generalization, the informaton) represents a fundamental quanta of an image's AIC, and an image's pixon basis represents the minimum degrees-of-freedom necessary to describ...

This paper reviews pixon-based image reconstruction, which in it current formulation uses a multiresolution language to quantify an image's Algorithmic Information Content (AIC) using Baye-sian techniques. Each pixon (or its generalization, the informaton) represents a fundamental quanta of an image's AIC, and an image's pixon basis represents the minimum degrees-of-freedom necessary to describ...

This paper describes the theory of pixon-based image reconstruction. After a brief introduction of the basic concepts of the pixon, the paper concentrates primarily on our current implementation of the techniques along with the approximations and shortcuts that seem to provide practical software algorithms. We then present an example of application of the method to astrophysical data.

Dimercaptosuccinic acid imaging is the 'gold standard' for the detection of cortical defects and diagnosis of scarring of the kidneys. The Siemens planar processing package, which implements adaptive noise reduction using the Pixon algorithm, is designed to allow a reduction in image noise, enabling improved image quality and reduced acquisition time/injected activity. This study aimed to estab...