حل اسئلة وسائط متعددة قسم الحاسوب الجامعة المستنصرية نموذج رقم1
Question #1/ Choose the correct answer (answer 15 only)
QUESTION #2/ Define the following: (answer five only) [10 Marks]
Question #3/ Answer A or B
Histogram: To draw the histogram, we count the frequency of each pixel intensity level in the image.
Pixel Intensity Level Frequency 0 2 1 2 2 1 3 1 4 1 6 1 7 1 The histogram visually represents the distribution of pixel intensities in the image.
Histogram Modification - Shrink for {Image (1,0)} with shrink max 6 & shrink min 1: Shrink is a histogram modification technique that adjusts the intensity levels of an image. The shrink operation compresses the intensity levels, mapping a wider range of intensities to a narrower range.
Here, we're focusing on the pixel value at position (1,0), which is 1.
Shrink Min: 1 Shrink Max: 6
The formula for shrink is: NewIntensity = ((OldIntensity - Min) / (Max - Min)) * NewMax
For the pixel at (1,0), the old intensity is 1, the minimum intensity is 1, the maximum intensity is 6, and the new maximum is 255 (assuming 8-bit grayscale).
NewIntensity = ((1 - 1) / (6 - 1)) * 255 = (0 / 5) * 255 = 0 * 255 = 0
So, the new intensity for pixel (1,0) after shrink operation is 0.
The neighborhood consists of the pixels with intensity values: 7, 1, 4, 3, 6, 0, 1, 0, 2.
To calculate the mean (average) intensity value of this neighborhood:
Mean = (7 + 1 + 4 + 3 + 6 + 0 + 1 + 0 + 2) / 9 = 24 / 9 ≈ 2.67
So, we would replace the intensity value of the pixel at (1,1) with the rounded mean value, which is approximately 3.
The modified image would look like this:
7 1 43 3 01 0 2
Let's say we want to resize it to a 5x5 image using ZOH. We'll duplicate each pixel horizontally and vertically:
7 7 1 1 47 7 1 1 43 3 6 6 03 3 6 6 01 1 0 0 2
QUESTION #4/ Answer the following: (answer two only)
Number of still images for two minutes = 30 images/second * 60 seconds/minute * 2 minutes = 3600 images
Total storage memory required = 3600 images * 2 megabytes/image = 7200 megabytes
Therefore, the storage memory required to store a two-minute video is 7200 megabytes.
Storage size in bytes = image width * image height * color depth
Storage size = 100 * 100 * (8 bits/channel * 3 channels) = 100 * 100 * 24 bits
Storage size in kilobytes (KB) = (Storage size in bytes) / 1024
Therefore, the image has 16,777,216 color levels, and the storage size is approximately 234.375 KB.
As you already pointed out, the first step is to sort the symbols by their frequency (count) in descending order:
| Symbol | Count |
|---|---|
| A | 14 |
| B | 9 |
| C | 8 |
| D | 7 |
| E | 5 |
2. Build the Shannon-Fano Tree:
- Start by combining the two symbols with the lowest frequencies. In this case, combine D (7) and E (5) to form a temporary node with a total count of 12.
- Now, we have four nodes: A (14), B (9), C (8), and the temporary node (D+E) (12).
- Combine the two nodes with the next lowest total counts. Since both B (9) and the temporary node (D+E) (12) have similar counts, we can choose either one arbitrarily. Here, let's combine B (9) and the temporary node (D+E) (12) to form another temporary node with a total count of 21.
- We are now left with three nodes: A (14) and the two temporary nodes (B+D+E) (21) and C (8).
- Finally, combine the remaining two nodes. Here, combine A (14) and the temporary node (B+D+E) (21) to form the root node with a total count of 35.
Shannon-Fano Tree Diagram:
(35)
/ \
(21) (14)
/ \
(12) (9)
/ \
(7) (5)
D E
B
3. Assign Codewords:
- Traverse the tree starting from the root. Assign a 0 (zero) to the left branch and a 1 (one) to the right branch at each level.
- For each symbol, follow the path from the root to its leaf node in the tree. The codeword for the symbol is the sequence of 0s and 1s encountered during this path.
Here's the table with assigned codewords:
| Symbol | Codeword |
|---|---|
| A | 1 |
| B | 01 |
| C | 00 |
| D | 000 |
| E | 001 |
4. Calculate Total Number of Bits:
- Multiply the frequency (count) of each symbol by the length of its codeword in bits.
- Sum the products for all symbols.
| Symbol | Count | Codeword Length | Product (Count * Length) |
|---|---|---|---|
| A | 14 | 1 | 14 |
| B | 9 | 2 | 18 |
| C | 8 | 2 | 16 |
| D | 7 | 3 | 21 |
| E | 5 | 3 | 15 |
Total Bits = 14 + 18 + 16 + 21 + 15 = 84 bits
(5) Compare between the following briefly (answer Two only)
Interactive Multimedia VS Hyper Media
Subtraction of two images VS Multiplication of two images
Image restoration VS image enhancement
Laplace filter VS Median filter
Sol//
| Feature | Interactive Multimedia | Hypermedia |
|---|---|---|
| User interaction | High, users can control content flow | Low, users navigate through predefined links |
| Examples | Games, simulations, e-learning | Educational websites, online encyclopedias |
| Feature | Subtraction of Two Images | Multiplication of Two Images |
|---|---|---|
| Operation | Subtracts corresponding pixel values | Multiplies corresponding pixel values |
| Result | Highlights differences between images | Creates a brighter or darker image depending on pixel values |
| Applications | Background subtraction, motion detection | Night vision enhancement, artistic effects |
| Feature | Image Restoration | Image Enhancement |
|---|---|---|
| Goal | Recover lost or corrupted image data | Improve the visual quality of an image |
| Examples | Removing noise, scratches, blurring | Adjusting contrast, brightness, sharpening |
| Applications | Restoring historical photographs, medical imaging | Creating visually appealing images for websites, presentations |
| Feature | Laplace Filter | Median Filter |
|---|---|---|
| Operation | Detects edges and high-frequency details | Removes noise while preserving edges |
| Applications | Edge detection, object recognition | Denoising images, removing salt-and-pepper noise |
QUESTION #5/ Explain the following: (answer five only)
Explanations for Multimedia Concepts:
(1) Post-production stage in a multimedia project:
This is the stage after the raw materials (video, audio, images, text) have been captured or created. It involves editing, processing, and combining all the elements to create the final multimedia product. Key tasks include:
- Editing: Assembling and arranging the captured footage, audio tracks, and other elements in a logical sequence.
- Adding effects: Applying transitions, filters, and special effects to enhance visual appeal.
- Color correction: Adjusting color balance, contrast, and brightness for better image quality.
- Audio mixing: Balancing audio levels, adding background music or sound effects, and incorporating narration.
- Encoding: Converting the final product into a specific format suitable for delivery (e.g., MP4, AVI).
(2) Compression System Model Diagram:
Here's a simple diagram representing a compression system model:
+------------+ +------------+
| Source | ------> | Encoder | ------> Compressed Data
+------------+ +------------+ (compressed format)
|
v
+------------+ +------------+
| Decoder | ------> | Sink |
+------------+ +------------+
|
v
+------------+ +------------+
| Destination| ------> | (Final Output)
+------------+ +------------+
- Source: The original uncompressed data (e.g., audio, video, image).
- Encoder: Analyzes the data and applies compression techniques to reduce its size.
- Compressed Data: The data in a smaller format after applying compression.
- Decoder: Receives the compressed data and decompresses it back to a usable format.
- Sink: The device or application that receives the final output (e.g., computer screen, speakers).
- Destination: The final form in which the data is presented (e.g., video displayed on a screen, audio played through speakers).
(3) Quantization of Audio:
This is a lossy compression technique used in audio encoding. It reduces the number of bits needed to represent an audio signal by grouping similar amplitude values into discrete levels (quantization bins). While this reduces the file size, it can introduce some loss of audio fidelity.
3) تكميم الصوت:
هذه تقنية ضغط مع فقدان البيانات تستخدم في تشفير الصوت. فهو يقلل من عدد البتات اللازمة لتمثيل إشارة صوتية عن طريق تجميع قيم السعة المماثلة في مستويات منفصلة (صناديق التكميم). على الرغم من أن هذا يقلل من حجم الملف، إلا أنه قد يؤدي إلى فقدان بعض الدقة في الصوت.
4) Keyframe-based animation:
This is a widely used animation technique where only the key poses or positions of an object are defined at specific points in time (keyframes). The software automatically interpolates (calculates) the in-between frames to create a smooth animation sequence. This approach simplifies the animation process and reduces file size compared to storing every single frame.
4) الرسوم المتحركة المستندة إلى الإطار الرئيسي:
هذه تقنية رسوم متحركة مستخدمة على نطاق واسع حيث يتم تحديد أوضاع أو مواضع المفتاح فقط للكائن في نقاط زمنية محددة (الإطارات الرئيسية). يقوم البرنامج تلقائيًا بإقحام (حساب) الإطارات البينية لإنشاء تسلسل رسوم متحركة سلس. يعمل هذا الأسلوب على تبسيط عملية الرسوم المتحركة وتقليل حجم الملف مقارنة بتخزين كل إطار على حدة.
(5) Advantages of digital video:
- Easy editing and manipulation: Digital video can be easily edited, trimmed, and combined using software tools.
- High quality and fidelity: Digital video offers superior image quality compared to analog formats, with less degradation over time.
- Copying and distribution: Digital video can be easily copied and distributed without loss of quality.
- Special effects and compositing: Digital video allows for advanced special effects and compositing techniques, creating visually stunning outcomes.
- Storage and accessibility: Digital video can be stored efficiently on hard drives or streamed online, making it readily accessible.
6) Advantages of using multimedia:
- Engages multiple senses: Multimedia presentations can engage viewers through sight, sound, and possibly even touch or interactivity, enhancing learning and retention.
- Information clarity and presentation: Multimedia elements (images, videos, audio) can help simplify complex information, making it easier to understand and remember.
- Increased user interaction: Interactive multimedia allows users to explore information at their own pace and control the flow of the presentation, promoting active learning.
- Appeal to different learning styles: Multimedia caters to different learning styles (visual, auditory, kinesthetic) by presenting information in multiple ways.
- More engaging and memorable: Multimedia presentations can be more engaging and memorable than traditional text-based formats.
(7) Data reduction in image analysis:
Data reduction is a crucial aspect in image analysis due to the large amount of data contained in an image. Common techniques include:
- Downsampling: Reducing the image resolution by discarding pixels.
- Color quantization: Reducing the number of colors in an image.
- Feature extraction: Extracting only relevant features (e.g., edges, shapes) from the image for analysis.
- Compression: Applying compression techniques to reduce file size without significantly impacting the information needed for analysis.
(8) Rendering:
Rendering is the process of converting 3D models, scenes, and animations into final images or videos. It involves calculating lighting, shadows, textures, and applying effects to create a realistic