![]() The („large format“) look that we see in this test is created not only by the format size but it’s a result of the combination of the sensor size the lens choice. The higher the resolution the higher is the spatial frequency which makes the noise appear more subtle. The perceived intensity of image noise depends not only on its standard deviation but also on its spatial frequency. The spatial frequency of the noise changes with the resolution of the sensor. In this case the SNR is higher and the image contains less noise. The stronger the resulting signal, the smaller the amount of shot noise compared to the entire signal. The larger a photosite is the more photons it can catch in a given amount of time which leads to a stronger signal. Arri is known for its especially large pixels that are very sensitive to light. Generally, there are many different kinds of image noise and they can have very different causes. Image noise can be described by the so-called Signal to Noise Ratio (SNR) which gives information about the relation between the whole signal and the amount of noise it contains. This is because they can have both a bigger and a higher count of photosites on their surface. Larger format sensors have the ability to produce less noise. ![]() Also, the mirror of the 3D rig affects both cameras‘ image quality (-1 stop of light, color tints, loss of contrast) so both cameras would perform slightly better under real shooting conditions. Anyway, it is important to keep in mind that the Alexa Mini doesn’t use its maximum potential in this test since its full sensor is actually bigger and has a higher resolution of 3424×2202 photosites. The same correction was necessary for the 35mm and 70mm focal lengths.Īfter the crop, the used sensor area of the Alexa Mini still counts at least 2740×1370 photosites which is approximately the same as in the regular 2K ProRes 4444 mode. Since most focal lengths on prime lenses only come in hard steps of (18, 25, 35, 50, etc.) I had to go with a 35mm DNA Prime instead of a 32mm on the Alexa 65. To match the resulting deviation of the angle of view I needed to crop the sensor of the Alexa Mini slightly. To get the same angle of view you would need to use an 18mm lens on the Alexa Mini and a 32 mm lens on the Alexa 65. In order to match the angle of view by focal length compensation, the focal length needs to be multiplied by the crop factor. Relative crop factor of the Alexa 65 to the Alexa Mini: Knowing these values, the crop factor can be calculated by dividing the sensors diagonals by each other: The Alexa Mini uses in ArriRaw 3.4K Open Gate mode (at 2:1 aspect ratio) a sensor area of 28.25 x 18.17 mm. The Alexa 65 uses in ArriRaw 6.5K Open Gate mode (at 2:1 aspect ratio) a sensor area of 51.15 x 25.58 mm. With Arri’s frame line and lens illumination tool, you can find out the actual used sensor area in different recording modes. The whole test was shot in a 2:1 aspect ratio which has to be considered in order to calculate the used sensor area. ![]()
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