How statement and proof provenance work
The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
- Literature-sourced: the exact statement appears in a cited source; only wording and notation differ.
- AI-adapted: a semantically identical restatement of literature-sourced material, modulo indexing, notation, and boundary cases adopted by the library.
- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Convexity, lower semicontinuity, and BV agreement of L² TV
Statement
Let be open and let be the extended distributional total variation on . It is proper, convex, lower semicontinuous in the norm, and positively one-homogeneous for nonnegative scalars. For every , it agrees with spatial TV: .
Statement references
Facts & Assumptions
Given: An open , the functional on , and the spatial BV total variation.
Distributional TV as an extended functional on L²: is the supremum of over smooth compactly supported vector fields with Euclidean norm at most one.
Test-field formula and L1 lower semicontinuity of spatial TV: for , equals the same test-field supremum.
Cauchy–Schwarz: , with equality exactly for dependent pairs: each test functional is continuous on , with absolute value at most .
Proof
The zero function has , so the functional is proper; its defining test class is symmetric under , hence its supremum is nonnegative. For , linearity of every test integral gives , and the equality also holds for . For , every admissible field gives ; taking the supremum proves convexity, with the extended-real cases automatic.
By [F3], every fixed test integral is a continuous linear functional on . For each real , the sublevel set is the intersection, over all admissible , of the closed half-spaces ; hence it is closed and is lower semicontinuous. If , [F1] and [F2] give .
Depends on
Used by
Dependency tree · two levels
17 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- José A. Iglesias, Gwenael Mercier, and Otmar Scherzer, A note on convergence of solutions of total variation regularized linear inverse problems, §1.1 (standard reference, not scraped)
- Gláucio Terra, Introduction to Geometric Measure Theory — Lecture Notes, version 1.6, §7.4 (standard reference, not scraped)