COMPOSITION
- 
Composition – These are the basic lighting techniques you need to know for photography and filmRead more: Composition – These are the basic lighting techniques you need to know for photography and filmhttp://www.diyphotography.net/basic-lighting-techniques-need-know-photography-film/ Amongst the basic techniques, there’s… 1- Side lighting – Literally how it sounds, lighting a subject from the side when they’re faced toward you 2- Rembrandt lighting – Here the light is at around 45 degrees over from the front of the subject, raised and pointing down at 45 degrees 3- Back lighting – Again, how it sounds, lighting a subject from behind. This can help to add drama with silouettes 4- Rim lighting – This produces a light glowing outline around your subject 5- Key light – The main light source, and it’s not necessarily always the brightest light source 6- Fill light – This is used to fill in the shadows and provide detail that would otherwise be blackness 7- Cross lighting – Using two lights placed opposite from each other to light two subjects 
- 
StudioBinder – Roger Deakins on How to Choose a Camera Lens — Cinematography Composition TechniquesRead more: StudioBinder – Roger Deakins on How to Choose a Camera Lens — Cinematography Composition Techniqueshttps://www.studiobinder.com/blog/camera-lens-buying-guide/ https://www.studiobinder.com/blog/e-books/camera-lenses-explained-volume-1-ebook 
DESIGN
COLOR
- 
GretagMacbeth Color Checker Numeric Values and Middle GrayRead more: GretagMacbeth Color Checker Numeric Values and Middle GrayThe human eye perceives half scene brightness not as the linear 50% of the present energy (linear nature values) but as 18% of the overall brightness. We are biased to perceive more information in the dark and contrast areas. A Macbeth chart helps with calibrating back into a photographic capture into this “human perspective” of the world. https://en.wikipedia.org/wiki/Middle_gray In photography, painting, and other visual arts, middle gray or middle grey is a tone that is perceptually about halfway between black and white on a lightness scale in photography and printing, it is typically defined as 18% reflectance in visible light  Light meters, cameras, and pictures are often calibrated using an 18% gray card[4][5][6] or a color reference card such as a ColorChecker. On the assumption that 18% is similar to the average reflectance of a scene, a grey card can be used to estimate the required exposure of the film. https://en.wikipedia.org/wiki/ColorChecker (more…)
- 
Capturing the world in HDR for real time projects – Call of Duty: Advanced WarfareRead more: Capturing the world in HDR for real time projects – Call of Duty: Advanced WarfareReal-World Measurements for Call of Duty: Advanced Warfare www.activision.com/cdn/research/Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf Local version Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf 
- 
Thomas Mansencal – Colour Science for PythonRead more: Thomas Mansencal – Colour Science for Pythonhttps://thomasmansencal.substack.com/p/colour-science-for-python https://www.colour-science.org/ Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science. It is freely available under the BSD-3-Clause terms. 
- 
Björn Ottosson – How software gets color wrongRead more: Björn Ottosson – How software gets color wronghttps://bottosson.github.io/posts/colorwrong/ Most software around us today are decent at accurately displaying colors. Processing of colors is another story unfortunately, and is often done badly. To understand what the problem is, let’s start with an example of three ways of blending green and magenta: - Perceptual blend – A smooth transition using a model designed to mimic human perception of color. The blending is done so that the perceived brightness and color varies smoothly and evenly.
- Linear blend – A model for blending color based on how light behaves physically. This type of blending can occur in many ways naturally, for example when colors are blended together by focus blur in a camera or when viewing a pattern of two colors at a distance.
- sRGB blend – This is how colors would normally be blended in computer software, using sRGB to represent the colors.
 Let’s look at some more examples of blending of colors, to see how these problems surface more practically. The examples use strong colors since then the differences are more pronounced. This is using the same three ways of blending colors as the first example. Instead of making it as easy as possible to work with color, most software make it unnecessarily hard, by doing image processing with representations not designed for it. Approximating the physical behavior of light with linear RGB models is one easy thing to do, but more work is needed to create image representations tailored for image processing and human perception. Also see: 
- 
sRGB vs REC709 – An introduction and FFmpeg implementationsRead more: sRGB vs REC709 – An introduction and FFmpeg implementations 1. Basic Comparison- What they are
- sRGB: A standard “web”/computer-display RGB color space defined by IEC 61966-2-1. It’s used for most monitors, cameras, printers, and the vast majority of images on the Internet.
- Rec. 709: An HD-video color space defined by ITU-R BT.709. It’s the go-to standard for HDTV broadcasts, Blu-ray discs, and professional video pipelines.
 
- Why they exist
- sRGB: Ensures consistent colors across different consumer devices (PCs, phones, webcams).
- Rec. 709: Ensures consistent colors across video production and playback chains (cameras → editing → broadcast → TV).
 
- What you’ll see
- On your desktop or phone, images tagged sRGB will look “right” without extra tweaking.
- On an HDTV or video-editing timeline, footage tagged Rec. 709 will display accurate contrast and hue on broadcast-grade monitors.
 
 
 2. Digging DeeperFeature sRGB Rec. 709 White point D65 (6504 K), same for both D65 (6504 K) Primaries (x,y) R: (0.640, 0.330) G: (0.300, 0.600) B: (0.150, 0.060) R: (0.640, 0.330) G: (0.300, 0.600) B: (0.150, 0.060) Gamut size Identical triangle on CIE 1931 chart Identical to sRGB Gamma / transfer Piecewise curve: approximate 2.2 with linear toe Pure power-law γ≈2.4 (often approximated as 2.2 in practice) Matrix coefficients N/A (pure RGB usage) Y = 0.2126 R + 0.7152 G + 0.0722 B (Rec. 709 matrix) Typical bit-depth 8-bit/channel (with 16-bit variants) 8-bit/channel (10-bit for professional video) Usage metadata Tagged as “sRGB” in image files (PNG, JPEG, etc.) Tagged as “bt709” in video containers (MP4, MOV) Color range Full-range RGB (0–255) Studio-range Y′CbCr (Y′ [16–235], Cb/Cr [16–240]) 
 Why the Small Differences Matter(more…)
- What they are
LIGHTING
- 
Light and Matter : The 2018 theory of Physically-Based Rendering and Shading by AllegorithmicRead more: Light and Matter : The 2018 theory of Physically-Based Rendering and Shading by Allegorithmicacademy.substance3d.com/courses/the-pbr-guide-part-1 academy.substance3d.com/courses/the-pbr-guide-part-2 Local copy:
 
- 
domeble – Hi-Resolution CGI Backplates and 360° HDRIRead more: domeble – Hi-Resolution CGI Backplates and 360° HDRIWhen collecting hdri make sure the data supports basic metadata, such as: - Iso
- Aperture
- Exposure time or shutter time
- Color temperature
- Color space Exposure value (what the sensor receives of the sun intensity in lux)
- 7+ brackets (with 5 or 6 being the perceived balanced exposure)
 In image processing, computer graphics, and photography, high dynamic range imaging (HDRI or just HDR) is a set of techniques that allow a greater dynamic range of luminances (a Photometry measure of the luminous intensity per unit area of light travelling in a given direction. It describes the amount of light that passes through or is emitted from a particular area, and falls within a given solid angle) between the lightest and darkest areas of an image than standard digital imaging techniques or photographic methods. This wider dynamic range allows HDR images to represent more accurately the wide range of intensity levels found in real scenes ranging from direct sunlight to faint starlight and to the deepest shadows. The two main sources of HDR imagery are computer renderings and merging of multiple photographs, which in turn are known as low dynamic range (LDR) or standard dynamic range (SDR) images. Tone Mapping (Look-up) techniques, which reduce overall contrast to facilitate display of HDR images on devices with lower dynamic range, can be applied to produce images with preserved or exaggerated local contrast for artistic effect. Photography In photography, dynamic range is measured in Exposure Values (in photography, exposure value denotes all combinations of camera shutter speed and relative aperture that give the same exposure. The concept was developed in Germany in the 1950s) differences or stops, between the brightest and darkest parts of the image that show detail. An increase of one EV or one stop is a doubling of the amount of light. The human response to brightness is well approximated by a Steven’s power law, which over a reasonable range is close to logarithmic, as described by the Weber�Fechner law, which is one reason that logarithmic measures of light intensity are often used as well. HDR is short for High Dynamic Range. It’s a term used to describe an image which contains a greater exposure range than the “black” to “white” that 8 or 16-bit integer formats (JPEG, TIFF, PNG) can describe. Whereas these Low Dynamic Range images (LDR) can hold perhaps 8 to 10 f-stops of image information, HDR images can describe beyond 30 stops and stored in 32 bit images.  
- 
9 Best Hacks to Make a Cinematic Video with Any CameraRead more: 9 Best Hacks to Make a Cinematic Video with Any Camerahttps://www.flexclip.com/learn/cinematic-video.html - Frame Your Shots to Create Depth
- Create Shallow Depth of Field
- Avoid Shaky Footage and Use Flexible Camera Movements
- Properly Use Slow Motion
- Use Cinematic Lighting Techniques
- Apply Color Grading
- Use Cinematic Music and SFX
- Add Cinematic Fonts and Text Effects
- Create the Cinematic Bar at the Top and the Bottom
  
- 
Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using FluxRead more: Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using Fluxhttps://civitai.com/models/735980/flux-equirectangular-360-panorama https://civitai.com/models/745010?modelVersionId=833115 The trigger phrase is “equirectangular 360 degree panorama”. I would avoid saying “spherical projection” since that tends to result in non-equirectangular spherical images. Image resolution should always be a 2:1 aspect ratio. 1024 x 512 or 1408 x 704 work quite well and were used in the training data. 2048 x 1024 also works. I suggest using a weight of 0.5 – 1.5. If you are having issues with the image generating too flat instead of having the necessary spherical distortion, try increasing the weight above 1, though this could negatively impact small details of the image. For Flux guidance, I recommend a value of about 2.5 for realistic scenes. 8-bit output at the moment   
COLLECTIONS
| Featured AI
| Design And Composition 
| Explore posts  
POPULAR SEARCHES
unreal | pipeline | virtual production | free | learn | photoshop | 360 | macro | google | nvidia | resolution | open source | hdri | real-time | photography basics | nuke
FEATURED POSTS
- 
4dv.ai – Remote Interactive 3D Holographic Presentation Technology and System running on the PlayCanvas engine
- 
Advanced Computer Vision with Python OpenCV and Mediapipe
- 
Key/Fill ratios and scene composition using false colors and Nuke node
- 
Image rendering bit depth
- 
Python and TCL: Tips and Tricks for Foundry Nuke
- 
Zibra.AI – Real-Time Volumetric Effects in Virtual Production. Now free for Indies!
- 
RawTherapee – a free, open source, cross-platform raw image and HDRi processing program
- 
Ross Pettit on The Agile Manager – How tech firms went for prioritizing cash flow instead of talent (and artists)
Social Links
DISCLAIMER – Links and images on this website may be protected by the respective owners’ copyright. All data submitted by users through this site shall be treated as freely available to share.











































