- Allows greater license to edit images, its scales and chemicals.
- Allows the user scope to experiment with images, with its flexibility allowing an environment for various changes.
- It is a significantly enhanced product in comparison to traditional darkroom photography offer more options to enhance, transform and manipulate images
Digital Camera Imaging Systems
An image capture system contains a lens and a detector, which is often a charged coupled device (CCD). This is a linear or matrix array of photosensitive electronic elements. A traditional film frame's measurements are normally 36 x 24 mm, while typically a CCD array is six times smaller, measuring 6 x 4 mm. As a result of the reduction in frame, a digital camera's lens system must be of a sufficient quality, to allow the condensation of the image to an area 36 times smaller.
Digital Camera Image Capture
On an area array sensor, thousands of microscopic photocells are placed on a grid, these analyse small portions of the image, formed by the lense system, to create picture elements by sensity light intensity.
Sensor Spatial Resolution
"Pixelization" occurs when the resolution of the sensor array is too low, giving a blurry effect. Increasing the number of cells in the sensor array increases the resolutions of the captured image. Sensor devices today tend to have more than one million cells.
Digital Camera Colour
Filters are placed over the photocells to capture images in a combination of red, green and blue. Each area assigned eight bits numbers, giving them 256 values for colours. Typically the range is from 0-255. Each colour is a combination of red, green and blue. Red for example is 255-0-0, green is 0-255-0 and blue is 0-0-255.
Shades of green, blue and red which aren't quite as vibrant can be achieved by reducing the value, such as changing the above red example from 255-0-0 to 128-0-0 would make the colour of red roughly half as strong.
Achieving other colours which are not red, green or blue is achieved by combining at least two of the red, green and blue options. For example. the colour purple is a combination of red and blue.
Digital Camera Optics
Before the light collected by the lens is focused on to the sensor array, it is passed through an optical low-pass filter, which serves to:
Moire Prevention and Removal
An image capture system contains a lens and a detector, which is often a charged coupled device (CCD). This is a linear or matrix array of photosensitive electronic elements. A traditional film frame's measurements are normally 36 x 24 mm, while typically a CCD array is six times smaller, measuring 6 x 4 mm. As a result of the reduction in frame, a digital camera's lens system must be of a sufficient quality, to allow the condensation of the image to an area 36 times smaller.
Digital Camera Image Capture
On an area array sensor, thousands of microscopic photocells are placed on a grid, these analyse small portions of the image, formed by the lense system, to create picture elements by sensity light intensity.
Sensor Spatial Resolution
"Pixelization" occurs when the resolution of the sensor array is too low, giving a blurry effect. Increasing the number of cells in the sensor array increases the resolutions of the captured image. Sensor devices today tend to have more than one million cells.
Digital Camera Colour
Filters are placed over the photocells to capture images in a combination of red, green and blue. Each area assigned eight bits numbers, giving them 256 values for colours. Typically the range is from 0-255. Each colour is a combination of red, green and blue. Red for example is 255-0-0, green is 0-255-0 and blue is 0-0-255.
Shades of green, blue and red which aren't quite as vibrant can be achieved by reducing the value, such as changing the above red example from 255-0-0 to 128-0-0 would make the colour of red roughly half as strong.
Achieving other colours which are not red, green or blue is achieved by combining at least two of the red, green and blue options. For example. the colour purple is a combination of red and blue.
Digital Camera Optics
Before the light collected by the lens is focused on to the sensor array, it is passed through an optical low-pass filter, which serves to:
- Exclude any picture data, beyond the sensor's resolution
- Compensate for false coloration caused by drastic changes to colour contrast
- Redruced infrared and other sources of non visible light, which may disturb the imaging process carried out by the server
Moire Prevention and Removal
- Moire is a repetitive pattern of wavy lines or circles which can appear on objects in digital captures.
- It tends to happen when the patter of the imaging chip in the camera matches the fibers or fine parallel details in an object.
- Some cameras incorporate anti-aliasing fitlers, which slightly blur tiny details of objects although others don't as it may compromise the level of image sharpness.
- Regardless of whether the filters exist, digital cameras have the ability to create more.
Digital Image Fundamentals
- Digital images are called bitmaps or raster-scan and are composed of an array (grid or matrix) of smaller units called pixels (picture elements)
- Every pixel in the digital image is a uniform patch or colour, but when on the display screen it is a phosphor dot or stripe, consisting of a mixture of red, blue and green
The Pixel
- The smallest digital image element manipulated by image processing software
- They are individually coloured but as a result of their finite size, the colouring of a subject is only approximate.
Bit Map Graphics
A bit-mapped colour image is represnted in a digital memory as an ordered array of groups of bits. Each group codes colour for single pixels on the screen, meaning each pixel requires 24 bits - 8 for red, 8 for green and 8 for blue.
If the resolution of the file is 640 x 480, with each pixel being represented by 24 bits, the image size would be as follows:
640 x 480 x 24 = 7372800 bits - approximately 7.4MB
Dynamic Range
In a visual scene, the dynamic range is typically the number of colours or shades of grey represented. However, in a digitised image it is fixed as the number of bits used to represent each pixel in an image. This determines the maximum number of colours or shades of grey in the image pallette, which is formed by the specific colours used.
Bit Depths:
1 bit depth: Only has two values, black or white. A process named half tone can help simulate the colour grey by the way it spaces the black and white pixels.
8 bit depth (grey): This bit depth can represent, 256 (2 to the power of 8) shades of grey
8 bit depth (colour): Similar to the directly above, except it can represent 256 colours rather than shades of grey
24 bit depth: Known as true colour, 8 bits are used to represent each of the three additive primary colours (red, green and blue) and each pixel can represent over 16 million (2 to the power of 24). It also removes any countering which is visible at inferior bit depths.
Colour Palette:
A system palette is used when a computer system predetermines the palette and the colours, for example 256 in an 8 bit image, are used for all images. The image's appearance can be aided by selecting the 256 colours most appropriate to that image. However, this adaptive palette can cause problems, when multiple images are attempting to displayed. One palette has to be chosen and stuck to, regardless of how appropriate it is. It may be advisable to use foresight when choosing a palette.
An optimised palette is better to use than a non-optimised palette. The colours are more natural appropriate to life than in a non optimised palette. There is also less contouring, making the image appear more clear. The colours used in a non-optimised palette tend to neglect natural effects such as shading and using an optimised palette makes the image appear more altogether realistic.
The Four Categorisations of Digital Image Processing:
1 bit depth: Only has two values, black or white. A process named half tone can help simulate the colour grey by the way it spaces the black and white pixels.
8 bit depth (grey): This bit depth can represent, 256 (2 to the power of 8) shades of grey
8 bit depth (colour): Similar to the directly above, except it can represent 256 colours rather than shades of grey
24 bit depth: Known as true colour, 8 bits are used to represent each of the three additive primary colours (red, green and blue) and each pixel can represent over 16 million (2 to the power of 24). It also removes any countering which is visible at inferior bit depths.
Colour Palette:
A system palette is used when a computer system predetermines the palette and the colours, for example 256 in an 8 bit image, are used for all images. The image's appearance can be aided by selecting the 256 colours most appropriate to that image. However, this adaptive palette can cause problems, when multiple images are attempting to displayed. One palette has to be chosen and stuck to, regardless of how appropriate it is. It may be advisable to use foresight when choosing a palette.
An optimised palette is better to use than a non-optimised palette. The colours are more natural appropriate to life than in a non optimised palette. There is also less contouring, making the image appear more clear. The colours used in a non-optimised palette tend to neglect natural effects such as shading and using an optimised palette makes the image appear more altogether realistic.
The Four Categorisations of Digital Image Processing:
- Analysis: Operations provide information such as colour count and intensity.
- Manipulation: Content altering operations such as cropping and colour changing.
- Enhancement: Improving quality, such as better contrast or heightening images
- Transformation: Alter geometry, such as rotation
Processing Digital Images:
Firstly, the image is converted from analogue to digital (digitisation) and placed in a frame buffer, from here the digital image processing operations take place in the computer before it is passed back out to a frame buffer, following on from this the colours (red, green and blue) are looked up and they are each converted back to analogue and then the image is displayed.
Histogram:
A histogram is a graph which analyses intensity levels of an image. The graph ranges from 0 to 255 in a typical 8 bit scale. An image with good contrast and dynamic range shows a full use of the intensity ranges, an image with good contrast shows some vacant intensities and a low contrast image shows a high number of vacant intensities. Histograms tend to showcase the fact that pixel intensity is either high or low, it is very rarely in the middle.
Transformation:
Digitial Image Processing allows rotation and free rotation of images. Rotation is changing the position by a 90 degree angle or a number of 90 degree angles. This is achieved by remapping pixel positions in the rows and columns. Free rotation is achieved by moving an image by an angle of your choice, which often changes the shape of the image, the interpolation works out an appropriate colour value for each pixel position in the outputted image.
Manipulation: block fill is achieved by selecting an area to change and pixel addresses are tested and modified.
Enhancement: Filtering puts a kernel to use, moving over the image in pixel by pixel steps. At each of these steps, the elements of the kernel multiply the current pixel value and are then tallied up to achieve new pixel output value. Depth can be useful to accentuate a particular part of an image as it blurs the surroundings. The smaller the depth, the more accentuated the subject becomes and the more blurry the surroundings become. Motion blur can also be added to images to give the effect than an image was taken at a time of high movement.
Transformation:
Digitial Image Processing allows rotation and free rotation of images. Rotation is changing the position by a 90 degree angle or a number of 90 degree angles. This is achieved by remapping pixel positions in the rows and columns. Free rotation is achieved by moving an image by an angle of your choice, which often changes the shape of the image, the interpolation works out an appropriate colour value for each pixel position in the outputted image.
Manipulation: block fill is achieved by selecting an area to change and pixel addresses are tested and modified.
Enhancement: Filtering puts a kernel to use, moving over the image in pixel by pixel steps. At each of these steps, the elements of the kernel multiply the current pixel value and are then tallied up to achieve new pixel output value. Depth can be useful to accentuate a particular part of an image as it blurs the surroundings. The smaller the depth, the more accentuated the subject becomes and the more blurry the surroundings become. Motion blur can also be added to images to give the effect than an image was taken at a time of high movement.
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