Rediscovering Ancient Stories Through Remote Sensing Technology

Chuong Tran 

Picture this: an ancient drawing, barely a whisper of its former self, etched onto a rock wall. Time has faded it, leaving only the faintest outlines. A standard photograph captures little more than a washed-out blur.

Now, imagine a tool, a kind of color sorcerer, born from the vast landscapes of JPL's remote sensing expertise (see reference below). This tool, Principal Component-Based Color Enhancement, is now being turned towards the delicate art of the past to coax out the hidden hues, revealing what was once lost.

Suddenly, the rock wall transforms. You begin to see:

• The Painter's Palette: Distinct paints emerge, their subtle differences now clear, even those that seemed identical to the naked eye.

• The Story of Layers: The drawing's history unfolds, revealing layers of creation, as if time itself is being peeled back.

• The Unseen Details: Faint lines and shapes, once ghostly apparitions, now stand defined, revealing the artist's intent.

• The Scars of Time: Damage and wear, the marks of centuries, are clearly visible, telling the story of the drawing's journey through time.

Reference

• Alley, Ronald. Algorithm Theoretical Basis Document for Decorrelation Stretch. AST06. 1996.

Recognizing that MATLAB is proprietary software, I developed this open-source Python implementation of the JPL algorithm for remote sensing analysis. Its output has been successfully cross-verified with my MATLAB results. The script and work instructions are detailed below.