![]() RawDigger where you are working with the histogram of the raw data itself. JPEG/TIFF/converter histograms are of raw data converted to the image vs. Unlike the in-camera histogram (which is based on the in-camera JPEG, meaning that it depends on the JPEG settings and not just on the RAW data), or the histogram in a raw converter, RawDigger shows the histogram for the actual RAW data, with not even white balance applied to it. Thus we both reduce the length of the structure, and raise the trustworthiness of our values, since we’re really rounding, which reduces the influence of noise and improves the perception of the shape of the data distribution.Īs you can see log scale for the vertical axis helps to see the bars which represent relatively small amounts of pixels that would be invisible in linear scale. A good start for a 12-bit camera is a bin size of 4, while for a 14-bit it’s 16. The width of the sub-range - bin size - is chosen based on the particular problem we are trying to solve. ![]() The width of the bar is equal to the width of the sub-range, and the height of it is equal to the number of pixels that assumed values from that sub-range. This way, we are making a bar not for each value, but for each sub-range. In this case, it makes more sense to count the amount of pixels that took the value from this sub-range as a way of averaging them out. This means that a pixel can take on not an exact value it should, but a value within a certain sub-range. Since the camera’s sensor is not an ideal measuring tool, but is in fact a real world object, the values we get from its pixels are subject to all sorts of fluctuations (due to innate defects, slight differences between the pixels, photon noise, read noise, thermal noise, etc.). First of all, the entire graph does not fit to a monitor screen, and second of all, even if it fits, it’s untrustworthy. The vertical axis represents the number of pixels that got that value. The horizontal axis of the histogram reflects the range of all the possible values for that camera. This is going to be our histogram with a step ( bin size) of 1, because we used each value from our range of 0 to 4095. Some common examples of such in-camera raw preprocessing include color channel preconditioning, lossy compression, and digital ISO which simply statches the histogram leaving voids. Note: There can be less than 4096 bars since it’s possible that some values from a given range got no pixels, like it is in the case of underexposure or raw data which was pre-processed in some way, right in the camera, before recording the raw file. When finished, we will get no more than 4096 bars. For each value (0.4095) we will be plotting a bar with the height equal to the number of pixels that assumed this given value. How do we proceed? We read the raw data and calculate how many pixels took the value of 0, 1, 2, etc. ![]() Let’s plot a histogram for the raw data of the image above. It is worth to determine maximum values for your camera for each ISO setting, including "intermediate" settings, that will help you with understanding how your camera light meter is calibrated, where the camera places the midtone, and how much headroom you have above the midtone. Note: maximum value may depend on ISO setting. Even for the same sensor various camera makes and models can have different maximum values. Those are by design, depending on particular hardware and firmware implementations. ![]() In real life a 12-bit camera may not reach 4095 maximum even for a grossly overexposed shot also, some cameras we consider to be 12-bit may have maximum values slightly larger than 4095. For a 12-bit camera (when we say 12-bit we mean the camera has a 12-bit analog-to-digital converter, ADC) RAW data for every pixel can assume values ranging from 0 (the pixel was not affected by light in any way or the effect was below the lower limit of the range) to 2 12 -1 = 4095 (the RAW data for the pixel has been clipped, or the pixel being saturated - that is, the pixel charge is above the upper limit of the range). Suppose that the camera we used is a 12-bit one. Each value in the set is nearly (less noise, flare, and effects at deep shadows and extreme highlights) directly proportional to the value of the light intensity, measured by the corresponding pixels of the camera sensor during exposure.Īs with any measurement device, light measurements here are also only within the certain range (the ranges can be switched, that is where the ISO setting often comes to play). What there is a set of RAW values, which are measurements of light, as if the sensor is composed of many light meters – one at each pixel location. When we shoot in RAW, then, if we use the common meaning of “picture” (as in something that can be directly viewed), there is none. It is a rendition of the raw data, not the raw data itself.
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