Against Late Fall Hardwoods, Green scores 39/100 (), while Summit scores 42/100 ().
Based on color alignment, breakup scale, and texture density, the AI sees an approximate 3-point lean toward Summit in this particular environment.
HECS Hunting Green and Killik Summit are both mixed-scale patterns, so they behave similarly from a scale point of view. HECS Hunting Green balances micro and macro elements, while Killik Summit leans toward larger, macro-scale blocks, which shifts how each holds up in close cover versus more open sightlines. They are also similar in overall density, so neither one is dramatically busier or more open. HECS Hunting Green holds a slightly broader scale spread, giving it a bit more range in tight brush and mid-distance openings.
HECS Hunting Green vs Killik Summit
HECS Hunting Green and Killik Summit have been analyzed using our CamoMatrix AI engine, which measures scale, density, and edge behavior directly from the flat pattern artwork. Both land in the mixed-scale category, meaning they balance fine texture with larger breakup blocks instead of living at one extreme. Density is similar, so neither pattern overwhelms the eye or leaves too much empty space. Edge work is alike as well — both mixes both hard and soft edges, which affects how smoothly (or abruptly) each pattern merges with real brush, trunks, and rocks. Killik Summit's numeric scale index runs slightly higher, nudging it a bit more toward macro breakup, while HECS Hunting Green stays finer on average. Killik Summit lands slightly higher on the density index, adding a bit more visual texture. That can help in chaotic or brushy terrain where extra breakup is useful. HECS Hunting Green carries more spread in our readings, which can make it more forgiving when moving between close-cover stands and semi-open edges. As always, these results come from flat pattern imagery. Real-world performance depends heavily on terrain, season, and how the garments fit and move.
This is a pattern-only comparison from flat artwork. Terrain, season, and real backgrounds will still push one or the other ahead in specific setups.
Learn how the CamoMatrix AI evaluates camouflage patterns
Defines the dominant size of shapes in the pattern.
Indicates which scale range the pattern leans toward overall.
How busy the pattern is with shapes and noise.
How hard or soft shape boundaries are.