This project implements a multi-phase pipeline to analyze video content by detecting hidden letters through motion filtering, extracting and denoising audio, and simulating interlaced video scanning with enhancement effects.

• Reads a video (video_with_letters.mp4)
• Converts frames to grayscale and applies frame differencing
• Filters out noisy frames with high motion
• Saves only meaningful binary motion masks revealing hidden content

📁 Output: motion_frames/mask_###.png
🕵️ Hidden Message Revealed: Hello From Colab

• Extracts audio from a video (video_with_audio.mp4)
• Reduces background noise using the noisereduce library
• Saves both original and denoised audio files

🎧 Output:

• audio_extracted.wav
• audio_denoised.wav

• Simulates odd/even field interlacing by manipulating scanlines
• Applies a zoom effect for emphasis on regions
• Creates a flicker effect by alternating interlaced frames
• Saves final video outputs and a comparison image

📹 Output:

• video_odd_interlaced.mp4
• video_even_interlaced.mp4
• video_flicker_effect.mp4
• extreme_zoom_interlaced_frame_comparison.png

• cv2 (OpenCV) – for video processing and image analysis
• matplotlib – for visualization
• numpy – for numerical operations
• moviepy – for audio extraction from video
• noisereduce – for audio denoising
• soundfile – for reading/writing audio files
• shutil, os – for file handling and zipping directories
• google.colab – for file uploads/downloads in Colab environment