One term that is popular in the era of digital photography is the histogram. This term can be found on most modern digital cameras and the image processing program in the computer. Histogram itself is actually a representation of a digital image that is displayed in the form of graphs and can be displayed on the screen when the camera preview (record mode) or can be displayed on the captured image (playback mode). Histogram feature is important in evaluating the accuracy of exposure, but for that we need to understand the meaning of the graph shown by the histogram.
Little mention of exposure, there are two extreme conditions that can occur when the camera's exposure settings are not right. The first condition is called over-exposure where the image becomes too bright, there is a loss of detail in bright areas (termed blown highlights). The second condition is under-exposure, in which the image is too dark, and the detail in the dark areas become lost. The function of the histogram is telling us about how the exposure held by the pictures we took. Although digital cameras have an LCD screen is sharp and bright, but the LCD screen can not always be relied upon as an accurate reference exposure. Sometimes the images on the LCD screen looks bright, but it turns darker actual results depending on the type and settings on the camera LCD. Arguably the histogram on a digital camera into a modern light meter precision, where the graph shown represents the actual value of the dark light capable captured by the camera sensor.
Histogram in general looks like in the example image above. The graph above has a dark light range of 256 levels from 0 (minimum) to 255 (maximum), with the assumption that the camera sensor has a dynamic range of 8 bits. Each pixel of the sensor chip will catch the light with different light-dark and graphics that appear in the histogram shows the number of pixels for each level starting from the value 0 to 255. A value of 0 which is located at the far left of the histogram indicates the darkest conditions (pure black), in the center of the histogram is a middle-gray / midtone (gray) and the far right represents the most light conditions (pure white) with a value of 255. How to view the histogram is to see the spread of the graph on the horizontal plane (left and right) and also see the number of pixels in the vertical plane.
Consider the example above. Histogram in the above example is more dominant on the left so that the image is represented by a graph of this kind tend to be dark. Peaks also appear very high graphics indicate clipping or under exposure. There are some parts of the picture are losing detail in dark areas (shadows). When the display of this kind is found before the photo is taken (when the preview), then we can do the exposure compensation to a positive direction so that the peak of the graph can be shifted from dark areas.
The picture above shows the histogram graph dominant on the right so that the picture will be too bright. The peak of the graphic on the right side is also very high in the area indicate clipping highlights due to over exposure. When this condition is experienced as a preview, exposure compensation can be performed in the negative direction so that its spread could be in the middle.
The picture above shows the histogram which has a dark and bright areas are equally dominant, usually occurs when the dynamic range of the object to be photographed is much wider than the dynamic range of the camera. For example, when shooting a landscape dominated by bright sky and dark land.
So basically no histogram is considered 'true' or 'standard' because of the shape histogram will always vary depending on the condition of the image represents. But as a comparison, an image that has high contrast and detail and did not experience under or over exposure will have a graphical form that spreads from a dark area to a bright area with peaks that do not experience clipping. Use the information displayed by the histogram as a means of evaluating exposures and know is there is no clipping region of a photograph.
Little mention of exposure, there are two extreme conditions that can occur when the camera's exposure settings are not right. The first condition is called over-exposure where the image becomes too bright, there is a loss of detail in bright areas (termed blown highlights). The second condition is under-exposure, in which the image is too dark, and the detail in the dark areas become lost. The function of the histogram is telling us about how the exposure held by the pictures we took. Although digital cameras have an LCD screen is sharp and bright, but the LCD screen can not always be relied upon as an accurate reference exposure. Sometimes the images on the LCD screen looks bright, but it turns darker actual results depending on the type and settings on the camera LCD. Arguably the histogram on a digital camera into a modern light meter precision, where the graph shown represents the actual value of the dark light capable captured by the camera sensor.
Histogram in general looks like in the example image above. The graph above has a dark light range of 256 levels from 0 (minimum) to 255 (maximum), with the assumption that the camera sensor has a dynamic range of 8 bits. Each pixel of the sensor chip will catch the light with different light-dark and graphics that appear in the histogram shows the number of pixels for each level starting from the value 0 to 255. A value of 0 which is located at the far left of the histogram indicates the darkest conditions (pure black), in the center of the histogram is a middle-gray / midtone (gray) and the far right represents the most light conditions (pure white) with a value of 255. How to view the histogram is to see the spread of the graph on the horizontal plane (left and right) and also see the number of pixels in the vertical plane.
Consider the example above. Histogram in the above example is more dominant on the left so that the image is represented by a graph of this kind tend to be dark. Peaks also appear very high graphics indicate clipping or under exposure. There are some parts of the picture are losing detail in dark areas (shadows). When the display of this kind is found before the photo is taken (when the preview), then we can do the exposure compensation to a positive direction so that the peak of the graph can be shifted from dark areas.
The picture above shows the histogram graph dominant on the right so that the picture will be too bright. The peak of the graphic on the right side is also very high in the area indicate clipping highlights due to over exposure. When this condition is experienced as a preview, exposure compensation can be performed in the negative direction so that its spread could be in the middle.
The picture above shows the histogram which has a dark and bright areas are equally dominant, usually occurs when the dynamic range of the object to be photographed is much wider than the dynamic range of the camera. For example, when shooting a landscape dominated by bright sky and dark land.
So basically no histogram is considered 'true' or 'standard' because of the shape histogram will always vary depending on the condition of the image represents. But as a comparison, an image that has high contrast and detail and did not experience under or over exposure will have a graphical form that spreads from a dark area to a bright area with peaks that do not experience clipping. Use the information displayed by the histogram as a means of evaluating exposures and know is there is no clipping region of a photograph.
