9/1/2023 0 Comments 16 bit picture converter![]() ![]() You could perform the conversion and check using various metrics if the information in the 8bit image is reduced. If you look at the maximum and minimum pixel values you may well be able to convert to an 8 bit image without loosing any data. One case where the resolution would be affected is if you had a 16 bit image with a bunch of pixels of pixel value x and another bunch of pixels with pixel values x + 1 and converting to an 8 bit image mapped the pixels to the same value 'y' then you would not be able to resolve the two sets of pixels. The maximum pixel value in an 8 bit unsigned grayscale image would be 2^8-1 The maximum pixel value in a 16 bit unsigned grayscale image would be 2^16-1 ![]() To convert 16bit to 8bit the number of pixels would be the same but the bit depth would change. ![]() A reduction in resolution would come from changing the number of pixels. Note that when ImageJ converts a 16-bit image as 8-bit (using the Image > Type menu), it "burns in" whatever display range mapping you currently have set in the Brightness/Contrast dialog, making the apparent pixel values into the actual 8-bit pixel values.Ĭhanging from a 16 bit image to an 8 bit image would potentially reduce the contrast but not necessarily the resolution. Similarly, converting to 8-bit is fine if you want to merely visualize in another application, but it would generally be wrong to perform quantitative analysis on the down-converted image. See the Fiji wiki's article on JPEG for more details. If you are going to do any quantitative analysis at all, I strongly advise not converting to JPEG. If you use the Bio-Formats plugin to import your images into ImageJ, you can check the "Autoscale" option to ensure this dynamic display range scaling happens automatically.Īs for whether to convert to JPEG: JPEG is a lossy compression format, which has its own problems. When you autoscale, it resets the display range to match the data range, making values 67 and below appear black, values 520 and above appear white, and everything in between scaled linearly. So all those values (57 to 520) will appear near black. 67 to 520, but stored as a 16-bit image (with potential values ranging from 0 to 65535), the default display range is also 0=black, 65535=white, and values in between scaled linearly. If your image has intensity values ranging from e.g. In other words, it is unlikely that your image is actually all 0 values, but rather the display range is probably not set to align with the data range. You can verify whether the actual data is there by moving the mouse over the image, and looking at the pixel probe output in the status bar area of the main ImageJ window. You can fix this by clicking on Image ▶ Adjust ▶ Brightness/Contrast. For example, on a 12-bit camera, the largest possible intensity value is 4095-but with 0 mapped to black and 65535 mapped to white, 4095 ends up (linearly) mapped to a very very dark gray, nearly invisible to the human eye. In that case, the display is scaled to the full 16-bit range (0 - 65535 intensity values), even though the actual data values typically span a much smaller range. This problem can arise when 12-bit, 14-bit or 16-bit images are loaded into ImageJ without autoscaling. From the ImageJ wiki's Troubleshooting page: ![]()
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