Presentation is loading. Please wait.

Presentation is loading. Please wait.

Resolution = the number of photosites (pixels) in the array of your sensor or the total number of buckets Bit Depth / Pixel Depth.

Similar presentations


Presentation on theme: "Resolution = the number of photosites (pixels) in the array of your sensor or the total number of buckets Bit Depth / Pixel Depth."— Presentation transcript:

1 Resolution = the number of photosites (pixels) in the array of your sensor or the total number of buckets Bit Depth / Pixel Depth

2 (megapixels = number of pixels on sensor) This sensor is composed of an array of photosensitive diodes called photosites that capture photons (subatomic light particles) and converts them to electrons, much like solar panels convert light to energy. This build up of electrons in each photosite is converted to a voltage or electrical charge that is measured in numbers (quantizing). * Up to this point the process is analog * The charge measure is converted through an algorithm (code) to digital data as a picture element or ‘pixel’. These pixels are then relayed in consecutive order and stored as an image on the camera’s memory as a file. These files can then be viewed on the camera in the LCD screen, or uploaded to a computer where they can also be viewed or manipulated with imaging software HOW IT WORKS

3 It is possible for all these sensors to be called HD (or have at least 1080 pixels across) but it is the size of the pixels that contributes to its pixel depth (or dynamic range) SENSOR SIZE

4 Compare the size of a DSLR sensor to a pocket camera or smartphone – the difference in sensor size is noticeable. From this you can conclude that the larger DSLR will accommodate a larger sensor, and in turn a larger sensor will produce the better picture. This is why resolution (# pixels) doesn’t matter solely, because a more advanced camera with a large sensor will trump the low-end point-and-shoot with a small sensor (and smaller pixels) even if both sport the same number of megapixels! With a small sensor, the pixels can’t capture as much light, so a pocket camera will produce images that have less dynamic range and never as clean as a DSLR. A camera with a larger sensor will also produce images with less noise, especially at high ISO. Of course, the tradeoff in image quality means more convenience. SENSOR SIZE

5 You may be photographing in raw rather than jpeg because you know that raw files contain more information and because they are unprocessed, giving you more flexibility. But how do they contain more information? Among other things, digital photography raw files are captured at a higher bit depth — depending on the camera, 12, 14 or 16 bit, compared to 8 bit for jpegs. Whether 12, 14 or 16, these higher bit-depth files potentially contain much more information than 8 bit files. So what is bit depth? For each pixel in your image, the tonal value or brightness of the scene you are photographing is stored in the image file on your memory card, along with the color. Computer files store information in zeros and ones. Bit depth refers to the number of digits used to measure the tonal information for each pixel. BIT DEPTH / PIXEL DEPTH AND DYNAMIC RANGE

6

7 Bit depth refers to how many digits the tonal information for each pixel is stored in. Imagine if your camera used a bit-depth of one: you would have one digit to store how dark each piece of the scene was, the only possible values would be 0 and 1, and the only two tones that could be represented are black and white:

8 If the file had a bit depth of two, there would be two digits, and the four values of 00, 01, 10, and 11 would be possible, so the image could have black, dark gray, light gray, and white: Histogram from image with bit depth of 2

9 Let’s jump to a file with a bit depth of 5, which allows 2 to the 5th, or 32 possible values from 00000 to 11111: Histogram for Image with Bit Depth of 5

10 Now let’s jump to 8, which allows 2 to the 8th, or 256 values, and is what a jpeg supports: Histogram of Image with Bit Depth of 8

11 IMAGE ADJUSTMENTS IN RAW Darkened and added contrast to 8 bit image begins to create choppy histogram and lost information. Histogram from 12 Bit Version with Darkening and Contrast Boost. Same adjustments leave better histogram, greater dynamic range.

12 To have this additional “editing headroom”, you have to capture a high bit-depth image, i.e. a raw file, and you have to enhance it as a high-bit depth file. It does no good to convert a raw file into 8 bit as you move into Photoshop to work it. While you are working in Lightroom or Camera Raw, your work on your raw file is in 16 bit (standardized to accomodate 12, 14 and 16). When you move a file from Lightroom to Photoshop, you need to ensure that the Photoshop file stays in 16 bit. In Lightroom, go to Edit or Lightroom>Preferences>External Editing, and set your PSD or TIFF preference to 16 bit. Higher bit depth files also potentially have a much larger number of colors: an 8-bit jpeg can represent around 16 million colors, whereas a high bit-depth file can represent over 28 billion. 16 million may seem like enough, but again, with heavy editing, you can see color banding or blotchiness in your photo. Your high-bit-depth photo with billions of potential colors will hold up much better. SHOOT & EDIT IN RAW FORMA


Download ppt "Resolution = the number of photosites (pixels) in the array of your sensor or the total number of buckets Bit Depth / Pixel Depth."

Similar presentations


Ads by Google