Digital Image:
- A digital image is a representation of a two dimensional image as a finite set of digital values, called picture elements or pixels.
- Pixel values typically represent gray levels, colours, heights, opacities etc.
- Remember digitization implies that a digital image is an approximation of a real scene.
Digital Image Processing:
- Digital image processing focuses on two major tasks.
- Improvement of pictorial information for human interpretation.
- Processing of image data for storage, transmission and representation for autonomous machine perception.
Phases of Image Processing:
1. Acquisition: It could be as simple as being given an image which is in digital form. It involves two steps i.e,. Scaling and color conversion.
1. Acquisition: It could be as simple as being given an image which is in digital form. It involves two steps i.e,. Scaling and color conversion.
2. Image Enhancement: It is amongest the simplest and most appealing in areas of image processing it is also used to extract some hidden details from an image and is subjective.
3. Image Restoration: It also deals with appealing of an image but it is objective(Restoration is based on mathematical or probabilistic model or image degradation).
4. Morphological Processing: It deals with tools for extracting image components that are useful in the representation and description of shape.
5. Segmentation: It includes partitioning an image into its constituent parts or objects. Autonomous segmentation is the most difficult task in image processing.
6. Object Recognition: It is a process that assigns a label to an object based on its descriptor.
7. Representation and Description: It follows output of segmentation stage, choosing a representation is only the part of solution for transforming raw data into processed data.
8. Image Compression: It involves in developing some functions to perform this operation. It mainly deals with image size or resolution.
9. Colour Image Processing: It deals with pseudocolor and full color image processing color models are applicable to digital image processing.
4. Morphological Processing: It deals with tools for extracting image components that are useful in the representation and description of shape.
5. Segmentation: It includes partitioning an image into its constituent parts or objects. Autonomous segmentation is the most difficult task in image processing.
6. Object Recognition: It is a process that assigns a label to an object based on its descriptor.
7. Representation and Description: It follows output of segmentation stage, choosing a representation is only the part of solution for transforming raw data into processed data.
8. Image Compression: It involves in developing some functions to perform this operation. It mainly deals with image size or resolution.
9. Colour Image Processing: It deals with pseudocolor and full color image processing color models are applicable to digital image processing.
Real Time Applications:
– Medical Visualization
– Industrial Inspection
– Machine/ Robot Vision
– Artistic Effects
Advantages:
- The use of digital image processing techniques has exploded and they are now used for all kinds of tasks in all kinds of areas
– Medical Visualization
– Industrial Inspection
– Machine/ Robot Vision
– Artistic Effects
 |
| Used to Improve Quality and Remove Noise |
 |
| Used for Boundary Detection(Original MRI Image of Dog Heart vs Edge Detection) |
 |
| Used for Number Plate Recognition for Speed Cameras |
 |
| Used in Finger Print Recognition |
 |
| Used in Artistic Effects to Make Images More Visually Appealing |
Advantages:
- It improves the visual quality of an image and the distribution of intensity.
- It can process an image in such a way that the result is more suitable than the original image.
- An image can be easily modified using a number of techniques.
Disadvantages:
- Digital cameras which are used for digital image processing have some drawbacks like memory card problems, higher cost, battery consumption.