CSC733 Image Processing Assignment Example Malaysia
This course is intended to give students a fundamental understanding of image processing, its most common techniques, and mathematical foundations. It is structured so that they can understand the underlying principles behind digital image formation while also learning about related technical aspects such as compression or enhancement in various industrial areas – all through hands-on projects! Upon completion, you should be competent in applying what was learned on an individual level without having any trouble pursuing research into new areas like this one if your interests demand it.
In this course, you will be working with image processing in Photoshop and After Effects. You’ll learn how to adjust exposure, color balance, or add creative effects like Distort & Transform. You’ll also learn how to animate these effects using the program After Effects. Once you have mastered the techniques in this course, you will be able to create your own images and videos from scratch. In addition, Photoshop is one of the most widely used image editing programs in the world, so learning its basics will help you immensely as a designer or filmmaker.
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This course will give you a solid foundation in the basics of photography that is sure to help boost your creative potential. Learn everything from understanding exposure, depth of field, ISO settings, color temperature, shutter speed, and more! Then you’ll learn how to shoot video on a DSLR camera with professional settings like aperture, white balance & focus. Next, you’ll learn how to edit your photos & videos in Adobe Lightroom, Photoshop & After Effects. You’ll start by learning basic editing techniques like color grading, exposure adjustments, and selective coloring. Finally, you will learn advanced effects that utilize the key tools in Photoshop including filters, blurs, motion tracking, layer masks, and more!
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In this course, there are many types of assignments given to students like a group project, individual assignment, and the solutions are provided by us. Upon completion of this course you should be able to:
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Assignment Brief 1: Explain the basic theories and concepts of image processing.
Image processing is one of the most adaptable fields in computer science. It’s best for things that are hard to quantify, like image enhancement or measurement.
The basics can be reduced to under three sentences. Ask what you want the processor to do with your picture, Markovian machine learning methods compare our digital images with numerous other images using logical process, and edge detection use thresholds on pixels of an image to classify border regions between two different objects in a picture as being either edges or non-edges.
Markovian machines are easy ways for processors to learn certain processes by analyzing patterns among hundreds of pictures that have already been processed digitally for years now which means they know how pictures are shaped generally. Modern processors use a combination of a Markovian machine learning algorithm and an edge detector to perform most image transforming tasks.
Assignment Brief 2: Demonstrate basic image processing techniques to improve or restore image appearance.
There are a number of image processing techniques that can be done to adjust how images appear. Depending on the type of adjustment you need, here is a list of tutorials or articles containing information about specific adjustments.
- Color correction
- Chromatic Aberration Correction
- Sharpen Image
- Blur Image.
Each image needs to be treated as an individual case because no two images share the same pixel values. To find out more, we’ll take a look at two example images to see how they were processed. The first example is made with the help of airbrush tools and digital brushes in Photoshop and was not preceded by any post-processing applications.
The second example is an image that was altered after its original capture through the use of additional processing software such as Photomatix Pro Version 3 for HDR production. Additional changes were made as well such as removing unwanted objects, adjusting contrast levels, and applying a slight blur effect.
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Assignment Brief 3: Apply proper techniques of image enhancement, restoration, compression and segmentation to solve real-life applications.
Image enhancement, restoration, compression and segmentation are specialized tasks that may be necessary in order to solve your real-life application.
Methods for image processing can be carried out on images that contain either an abundance of information or insufficient amount of information. When the latter occurs, there is usually some level of ambiguity present whereby parts of the scene cannot be properly interpreted by researchers without using additional context clues (e.g., sensor values). Efforts in image segmentation today aim to dissect scenes with this sort of ambiguity into discernible objects so as to help researchers understand what they may otherwise never succeed at doing solely with light intensity readings alone. This is not an easy task and segmentation is a difficult problem that requires much attention when it comes to methodologies.
The goal of image segmentation is to partition an image into multiple segments, objects or regions that are relatively homogeneous given the information provided by the input intensity pattern. From each region, one can estimate properties such as color, texture and shape to establish a better understanding of what is being analyzed.
Image compression is the process of removing information from an image to reduce its file size and save transmission time. There are two types of image compression, lossy and lossless. Lossy means that data is removed or discarded in order to reduce the size or quality, the theory being that the consumer will not notice these minor details once they have seen what they wanted to see. Lossless means there is no reduction in quality – but also no reduction in file size either.
Assignment Brief 4: Evaluate image processing problems and select solutions
Many problems with photos can be fixed in their RAW environments by restoring the brightness and contrast to the image, adjusting the color balance, and then sharpening it. If this still doesn’t help satisfactorily, then try experimenting with different filters or tools that may fix any issues in transparency or motion in the picture. Some of these changes can include adding noise if transparency is difficult to see, but just know that this will result in “busy” looking images. I recommend using noise reduction for this instead if you want to avoid excessively “busy” looking images. In some cases, you will need to resize your image before inserting it into a document.
Image processing problems can be either cosmetic or affect proper operation of a device. Cosmetic damage is easily fixed through interpolation techniques where missing pixels are replaced with the nearest-known pattern from a bitmap file. The trouble comes when image processing fails to correctly interpret data due to information being lost during disc compression. This problem corrects itself as more data is sent by the original sender and received by receiver, but it also reviews how big a problem noise is because noise can distort the signal from which important information needs to be interpreted. It’s why radio waves have been used for years as an efficient means of communication for this reason – pure static creates too many problems that hinder the ability to decode data.
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