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brain twisting
Your brain makes use of remembered data and patterns in memory to find matches or identify when it encounters something new or unfamiliar. Take a good look at the image above. At first glance it just looks like a random collection of black splodges, but look longer and your brain may begin assembling a pattern familiar to it from memory.
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Rec-2020 – TVs new color gamut standard used by Dolby Vision?
https://www.hdrsoft.com/resources/dri.html#bit-depth
The dynamic range is a ratio between the maximum and minimum values of a physical measurement. Its definition depends on what the dynamic range refers to.
For a scene: Dynamic range is the ratio between the brightest and darkest parts of the scene.
For a camera: Dynamic range is the ratio of saturation to noise. More specifically, the ratio of the intensity that just saturates the camera to the intensity that just lifts the camera response one standard deviation above camera noise.
For a display: Dynamic range is the ratio between the maximum and minimum intensities emitted from the screen.
The Dynamic Range of real-world scenes can be quite high — ratios of 100,000:1 are common in the natural world. An HDR (High Dynamic Range) image stores pixel values that span the whole tonal range of real-world scenes. Therefore, an HDR image is encoded in a format that allows the largest range of values, e.g. floating-point values stored with 32 bits per color channel. Another characteristics of an HDR image is that it stores linear values. This means that the value of a pixel from an HDR image is proportional to the amount of light measured by the camera.
For TVs HDR is great, but it’s not the only new TV feature worth discussing.
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Intel Open Image Denoise High-Performance Denoising Library for Ray Tracing – pipeline
The purpose of Open Image Denoise is to provide an open, high-quality, efficient, and easy-to-use denoising library that allows one to significantly reduce rendering times in ray tracing based rendering applications. It filters out the Monte Carlo noise inherent to stochastic ray tracing methods like path tracing, reducing the amount of necessary samples per pixel by even multiple orders of magnitude (depending on the desired closeness to the ground truth).
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Ben Gunsberger – AI generated podcast about AI using Google NotebookLM
Listen to the podcast in the post
“I just created a AI-Generated podcast by feeding an article I write into Google’s NotebookLM. If I hadn’t make it myself, I would have been 100% fooled into thinking it was real people talking.”
