All Program of 6th Sem Digital Image Processing Lab with their Image Outputs. These Program includes Histogram, Histogram-Equalization, Transformation, Airthmetic-Operations, Log-Transformation, Power-Law-Transformation performing on an Image.
The Digital Image Processing (DIP) Lab at Rajasthan Technical University (RTU) is designed to provide students with hands-on experience and practical understanding of fundamental concepts and techniques in digital image processing. This lab complements theoretical coursework by enabling students to implement, analyze, and visualize various image processing algorithms using simulation tools and programming environments such as MATLAB and Java.
- To understand the basics of digital images, including image representation, sampling, and quantization.
- To explore spatial and frequency domain processing techniques for image enhancement and restoration.
- To implement image transformations such as Fourier, Walsh, Hadamard, and Discrete Cosine Transforms.
- To apply histogram processing, contrast stretching, and intensity transformations for image enhancement.
- To perform image segmentation, including edge detection, morphological operations, and region-based segmentation.
- To study image compression techniques and image restoration methods.
- To develop mini projects related to biometric security, medical imaging, texture analysis, and boundary detection.
The lab exercises include but are not limited to:
- Simulation and display of images, including negative and grayscale conversions.
- Implementation of pixel relationships and image transformations.
- Contrast enhancement using histogram equalization.
- Frequency domain filtering and Fast Fourier Transform (FFT).
- Application of smoothing and sharpening filters.
- Edge detection algorithms including gradient and Canny methods.
- Image compression using DCT, DPCM, and Huffman coding.
- Image segmentation techniques and morphological processing.
- Image restoration and intensity slicing for enhancement.
By the end of this lab, students will be able to:
- Develop and test image processing algorithms.
- Analyze the effects of different image processing techniques on real-world images.
- Understand the mathematical foundations behind image transformations and filtering.
- Apply image processing methods to solve practical problems in areas such as medical imaging, security, and multimedia.
- MATLAB for simulation and algorithm development.
- Image processing libraries and toolkits for Java or other programming languages.
- Access to image datasets for experimentation.