[SR NO 22] Resolve Image Processing Performance Degradation and Memory Leaks

[priyankeshh]

Closes #351

---

Overview

This PR optimizes image processing performance and stability by improving the adjust_brightness_contrast function and caching system. The changes resolve memory leaks, CPU bottlenecks, and inefficient cache management, significantly boosting speed and reducing resource consumption.

---

Original Issues & Performance Bottlenecks

1️⃣ Memory Leaks

• The image cache grew indefinitely without limits or cleanup, causing high memory usage.
• Cached images persisted until restart, leading to out-of-memory (OOM) errors.
• No eviction policy, so unused images stayed in memory indefinitely.

2️⃣ CPU Bottlenecks

• Inefficient LUT (Lookup Table) calculations slowed down processing.
• No parallel processing, leading to longer execution times for large images.
• Redundant pixel calculations caused unnecessary CPU overhead.

3️⃣ Cache Inefficiencies

• Weak cache key generation led to potential collisions and incorrect image retrieval.
• No invalidation strategy, so outdated images remained in cache.
• Unmanaged cache size, allowing excessive memory usage.

---

Optimizations & Solutions

✅ 1. Memory Leak Fixes

✔ Implemented Cache Size Limits → Prevents cache from exceeding memory constraints.
✔ LRU (Least Recently Used) Eviction Policy → Removes least-accessed images automatically.
✔ Cache Invalidation Mechanism → Removes stale entries using a Time-To-Live (TTL) policy.

✅ 2. CPU Performance Enhancements

✔ Optimized LUT Calculations → Pre-computed LUTs reduce expensive recalculations.
✔ Enabled Parallel Processing → Uses Rayon for multi-threaded execution, significantly boosting speed.
✔ Removed Redundant Pixel Operations → Cuts down unnecessary computations.

✅ 3. Improved Cache Management

✔ More Robust Cache Key Generation → Uses image dimensions, pixel data, and operation parameters to prevent collisions.
✔ Cache Size Management → Actively evicts entries when size limits are exceeded.
✔ Cache Invalidation Strategy → Ensures outdated images are removed automatically.

🚀 Performance:

You can check the benchmark results by running:

cd frontend/src-tauri/
cargo run --example benchmark_runner

[Ashutoshx7]

@priyankeshh linting test failed can u make a commit fixing this make sure to have proper structure and spacing

[priyankeshh]

@priyankeshh linting test failed can u make a commit fixing this make sure to have proper structure and spacing

The linting error is happening due to this core folder which has ai generated code. I can delete that folder and make the commit which will fix it